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Dagstuhl Seminar on Inductive Programming
The 7th AAIP Workshop on Approaches and Applications of Inductive Programming is accepted as Dagstuhl Seminar 17382 and will take place September 17 to 20, 2017. The workshop is jointly organized by Ute Schmid (University of Bamberg), Stephen Muggleton (Imperial College London), and Rishabh Singh (MIT and Microsoft Research).
For more information, see the Dagstuhl Seminar Page.
RuleML Blog Report about Dagstuhl Seminar AAIP'16
AAIP'16 in the RuleML Blog
http://via.aayo.ws/YmI4J
CACM on Inductive Programming
The review article “Inductive programming meets the real world” by
Gulwani,
Hernández-Orallo,
Kitzelmann,
Muggleton,
Schmid, and
Zorn
has been published in the Communications of the ACM, Vol. 58 No. 11, Pages 90-99. 10.1145/2736282
see fulltext
Wikipedia Page on Inductive Programming
José Hernández-Orallo and Ute Schmid created Wikipedia articles for Inductive Programming and Inductive Functional Programming.
Dagstuhl Seminar "Approaches and Applications of Inductive Programming"
José Hernández-Orallo (Polytechnic University of Valencia, ES), Stephen H. Muggleton (Imperial College London, GB), Ute Schmid (Universität Bamberg, DE) and Benjamin Zorn (Microsoft Research - Redmond, US) organize Dagstuhl Seminar 15442 "Approaches and Applications of Inductive Programming" scheduled for October 25 to 30, 2015.
The seminar is a continuation of the AAIP workshop series.
Please visit the AAIP 15 Homepage.
Report of Dagstuhl Seminar
We're pleased to inform you that the report of Dagstuhl Seminar 13502 is now published as part of the periodical Dagstuhl Reports.
The report is available online at the DROPS Server.
Dagstuhl Seminar "Approaches and Applications of Inductive Programming"
Ute Schmid (University of Bamberg), Emanuel Kitzelmann (University of Duisburg-Essen), Sumit Gulwani (Microsoft Research) and Marcus Hutter (Austrian National University) organize Dagstuhl Seminar 13502 "Approaches and Applications of Inductive Programming" scheduled for Monday, December 09 to December 11, 2013. The seminar is a continuation of the AAIP workshop series.
Please visit the AAIP 13 Homepage.
4th Workshop AAIP 2011
Ute Schmid and Emanuel Kitzelmann organize the 4th Workshop on Approaches and Applications of Inductive Programming. It will take place on July 19, 2011, in Odense, Denmark. Co-located events are the 13th International ACM SIGPLAN Symposium on Principles and Practice of Declarative Programming (PPDP 2011) and the 21st International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2011).
Details can be found on the AAIP 2011 Homepage.
Publications
Here's a comprehensive list of inductive programming
publications.
If you wish your publications to be added, or some
important papers are missing, then please send a message with the BibTex
entries to the admin.
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Ramiro Aguilar, Luis Alonso, Vivian Lòpez, and María N. Moreno.
Incremental discovery of sequential patterns for grammatical
inference.
In Emanuel Kitzelmann, Roland J. Olsson, and Ute Schmid, editors,
AAIP'05: Proceedings of the 1st Workshop on Approaches and
Applications of Inductive Programming (Bonn, Germany, Aug.7, 2005), pages
59-67, 2005.
Work in Progress Reports.
@inproceedings{aguilar_ea:2005, author = {Ramiro Aguilar and Luis Alonso and Vivian L\`opez and Mar\'ia N. Moreno}, title = {Incremental discovery of sequential patterns for grammatical inference}, editor = {Emanuel Kitzelmann and Roland J. Olsson and Ute Schmid}, booktitle = {{AAIP'05}: Proceedings of the 1st Workshop on Approaches and Applications of Inductive Programming (Bonn, Germany, Aug.\,7, 2005)}, year = 2005, pages = {59--67}, note = {Work in Progress Reports}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/aaip05/proceedings/artirami.pdf} }
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David W. Aha.
Case-based learning algorithms.
In I. Bareiss, R. Lewis, and S. Gravitis, editors, Proceedings
of the DARPA Case-Based Reasoning Workshop (Pensacola Beach, Florida,
May-June, 1989), volume 1, pages 147-158, Washington, D. C., 1991. Morgan
Kaufmann.
@inproceedings{aha:1991, author = {Aha, David W.}, title = {Case-Based Learning Algorithms}, editor = {I. Bareiss and R. Lewis and S. Gravitis}, booktitle = {Proceedings of the {DARPA} Case-Based Reasoning Workshop (Pensacola Beach, Florida, May--June, 1989)}, year = 1991, volume = 1, pages = {147--158}, address = {Washington, D. C.}, publisher = {Morgan Kaufmann} }
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David W. Aha, Charles X. Ling, Stan Matwin, and S. Lapointe.
Learning singly-recursive relations from small datasets.
In Ruzena Bajcsy, editor, IJCAI'93: Proceedings of the 13th
International Joint Conference on Artificial Intelligence (Chambéry,
France, Aug.28-Sep.3, 1993), pages 47-58. Morgan Kaufmann, 1993.
@inproceedings{aha_ea:1993, author = {David W. Aha and Charles X. Ling and Stan Matwin and S. Lapointe}, title = {Learning Singly-recursive Relations from Small Datasets}, editor = {Ruzena Bajcsy}, booktitle = {{IJCAI}'93: Proceedings of the 13th International Joint Conference on Artificial Intelligence (Chamb\'ery, France, Aug.\,28--Sep.\,3, 1993)}, year = 1993, pages = {47--58}, publisher = {Morgan Kaufmann} }
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David W. Aha, Stephane Lapointe, Charles X. Ling, and Stan Matwin.
Inverting implication with small training sets.
In Francesco Bergadano and Luc De Raedt, editors, Machine
Learning: ECML-94. European Conference on Machine Learning, Catania, Italy,
April6-8, 1994. Proceedings, volume 784 of Lecture Notes in Computer
Science, pages 29-48, Berlin/Heidelberg, 1994. Springer.
@inproceedings{aha_ea:1994, author = {David W. Aha and Stephane Lapointe and Charles X. Ling and Stan Matwin}, title = {Inverting Implication with Small Training Sets}, editor = {Bergadano, Francesco and De~Raedt, Luc}, booktitle = {Machine Learning: {ECML-94}. European Conference on Machine Learning, Catania, Italy, April\,6--8, 1994. Proceedings}, year = 1994, series = {Lecture Notes in Computer Science}, volume = 784, pages = {29--48}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, keywords = {CRUSTACEAN; ilp; inductive programming; ip-system; program synthesis; recursion}, abstract = {We present an algorithm for inducing recursive clauses using inverse implication (rather than inverse resolution) as the underlying generalization method. Our approach applies to a class of logic programs similar to the class of primitive recursive functions. Induction is performed using a small number of positive examples that need not be along the same resolution path. Our algorithm, implemented in a system named CRUSTACEAN, locates matched lists of generating terms that determine the pattern of decomposition exhibited in the (target) recursive clause. Our theoretical analysis defines the class of logic programs for which our approach is complete, described in terms characteristic of other ILP approaches. Our current implementation is considerably faster than previously reported. We present evidence demonstrating that, given randomly selected inputs, increasing the number of positive examples increases accuracy and reduces the number of outputs. We relate our approach to similar recent work on inducing recursive clauses.}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-57868-0}, url = {http://www.springerlink.com/content/p77364661un577p7/}, doi = {10.1007/3-540-57868-4_49} }
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David W. Aha, S. Lapointe, Charles X. Ling, and Stan Matwin.
Learning recursive relations with randomly selected small training
sets.
In Wiliam W. Cohen and Haym Hirsh, editors, ICML'94:
Proceedings of the 11th International Conference on Machine Learning (Rutgers
University, New Brunswick, NJ, USA, July10-13, 1994), pages 12-18.
Morgan Kaufmann, 1994.
@inproceedings{aha_ea:1994b, author = {David W. Aha and S. Lapointe and Charles X. Ling and Stan Matwin}, title = {Learning Recursive Relations with Randomly Selected Small Training Sets}, editor = {Wiliam W. Cohen and Haym Hirsh}, booktitle = {{ICML'94}: Proceedings of the 11th International Conference on Machine Learning (Rutgers University, New Brunswick, NJ, USA, July\,10--13, 1994)}, year = 1994, pages = {12--18}, publisher = {Morgan Kaufmann}, isbn = {1-55860-335-2} }
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Z. Alexin, T. Gyimothy, and H. Boström.
Integrating algorithmic debugging and unfolding transformation in an
interactive learner.
In W. Wahlster, editor, ECAI'96: Proceedings of the 12th
European Conference on Artificial Intelligence (Budapest), pages 403-407,
1996.
@inproceedings{alexin_ea:1996, author = {Alexin, Z. and Gyimothy, T. and Bostr\"{o}m, H.}, title = {Integrating Algorithmic Debugging and Unfolding Transformation in an Interactive Learner}, editor = {W. Wahlster}, booktitle = {{ECAI'96}: Proceedings of the 12th European Conference on Artificial Intelligence (Budapest)}, year = 1996, pages = {403--407}, keywords = {SPECTRE; algorithmic debugging; debugging; ilp; inductive programming; ip-system; program synthesis} }
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Saul Amarel.
Program synthesis as a theory formulation task: Problem
representations and solution methods.
In Ryszard S. Michalski, Jaime G. Carbonell, and Tom M. Mitchell,
editors, Machine Learning. An Artificial Intelligence Approach,
volume 2, chapter 18, pages 499-568. Morgan Kaufmann, Los Altos, CA, 1986.
@incollection{amarel:1986, author = {Saul Amarel}, title = {Program synthesis as a theory formulation task: Problem representations and solution methods}, editor = {Ryszard S. Michalski and Jaime G. Carbonell and Tom M. Mitchell}, booktitle = {Machine Learning. An Artificial Intelligence Approach}, publisher = {Morgan Kaufmann}, year = 1986, volume = 2, chapter = 18, pages = {499--568}, address = {Los Altos, CA}, annote = {ute-inflit} }
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John R. Anderson and Christian Lebiere.
The Atomic Components of Thought.
Lawrence Erlbaum Associates, Inc., 1998.
@book{anderson/lebiere:1998, author = {John R. Anderson and Christian Lebiere}, title = {The Atomic Components of Thought}, publisher = {Lawrence Erlbaum Associates, Inc.}, year = 1998, keywords = {cognition} }
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John R. Anderson, R. Farrell, and R. Sauers.
Learning to program in lisp.
Cognitive Science, 8:87-129, 1984.
@article{anderson_ea:1984, author = {John R. Anderson and R. Farrell and R. Sauers}, title = {Learning to program in LISP}, journal = {Cognitive Science}, year = 1984, volume = 8, pages = {87--129}, annote = {ute-psylit} }
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John R. Anderson, F. G. Conrad, and A. T. Corbett.
Skill acquisition and the LISP tutor.
Cognitive Science, 13:467-505, 1989.
@article{anderson_ea:1989, author = {John R. Anderson and F. G. Conrad and A. T. Corbett}, title = {Skill acquisition and the {LISP} tutor}, journal = {Cognitive Science}, year = 1989, volume = 13, pages = {467--505}, annote = {ute-psylit} }
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Dana Angluin and Carl H. Smith.
Inductive inference: Theory and methods.
Computing Surveys, 15(3):237-269, 1983.
@article{angluin/smith:1983, author = {Dana Angluin and Carl H. Smith}, title = {Inductive Inference: Theory and Methods}, journal = {Computing Surveys}, year = 1983, volume = 15, number = 3, pages = {237--269}, address = {New York, NY, USA}, publisher = {{ACM}}, keywords = {1980; Angluin; Smith; article; identification in the limit; inductive inference; overview; survey}, issn = {0360-0300}, url = {http://doi.acm.org/10.1145/356914.356918} }
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Dana Angluin.
Finding patterns common to a set of strings (extended abstract).
In STOC'79: Proceedings of the 11th annual ACM symposium on
Theory of computing (Atlanta, Georgia, USA, April30-May02, 1979), pages
130-141, New York, NY, USA, 1979. ACM.
@inproceedings{angluin:1979, author = {Dana Angluin}, title = {Finding patterns common to a set of strings (Extended Abstract)}, booktitle = {{STOC'79}: Proceedings of the 11th annual {ACM} symposium on Theory of computing (Atlanta, Georgia, USA, April\,30--May\,02, 1979)}, year = 1979, pages = {130--141}, address = {New York, NY, USA}, publisher = {{ACM}}, keywords = {1979; Angluin; inproceedings; pattern languages}, annote = {Finding patterns common to a set of strings (Extended Abstract)}, url = {http://doi.acm.org/10.1145/800135.804406}, abstract = {We motivate, formalize, and study a computational problem in concrete inductive inference. A ``pattern'' is defined to be a concatenation of constants and variables, and the language of a pattern is defined to be the set of strings obtained by substituting constant strings for the variables. The problem we consider is, given a set of strings, find a minimal pattern language containing this set. This problem is shown to be effectively solvable in the general case and to lead to correct inference in the limit of the pattern languages. There exists a polynomial time algorithm for it in the restricted case of one-variable patterns. Inference from positive data is re-examined, and a characterization given of when it is possible for a family of recursive languages. Various collateral results about patterns and pattern languages are obtained. Section 1 is an introduction explaining the context of this work and informally describing the problem formulation. Section 2 is definitions. Section 3 is results concerning patterns and pattern languages. Section 4 concerns the abstract question of inference from positive data. Section 5 gives a polynomial time algorithm for finding minimal one-variable pattern languages compatible with a given set of strings. Section 6 contains remarks.} }
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Dana Angluin.
Queries and concept learning.
Machine Learning, 2(4):319-342, April 1988.
@article{angluin:1988, author = {Dana Angluin}, title = {Queries and Concept Learning}, journal = {Machine Learning}, year = 1988, volume = 2, number = 4, pages = {319--342}, month = {April}, keywords = {Concept learning; supervised learning; queries}, abstract = {We consider the problem of using queries to learn an unknown concept. Several types of queries are described and studied: membership, equivalence, subset, superset, disjointness, and exhaustiveness queries. Examples are given of efficient learning methods using various subsets of these queries for formal domains, including the regular languages, restricted classes of context-free languages, the pattern languages, and restricted types of prepositional formulas. Some general lower bound techniques are given. Equivalence queries are compared with Valiant's criterion of probably approximately correct identification under random sampling.}, publisher = {Springer}, address = {Netherlands}, issn = {0885-6125 (Print) 1573-0565 (Online)}, url = {http://www.springerlink.com/content/u228266621966h58/}, doi = {10.1023/A:1022821128753} }
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Dana Angluin.
Equivalence queries and approximate fingerprints.
In COLT'89: Proceedings of the 2nd Annual Workshop on
Computational Learning Theory (Santa Cruz, CA, USA, July31-Aug.2,
1989), pages 134-145, San Francisco, CA, USA, 1990. Morgan Kaufmann.
@inproceedings{angluin:1990, author = {Dana Angluin}, title = {Equivalence Queries and Approximate Fingerprints}, booktitle = {{COLT'89}: Proceedings of the 2nd Annual Workshop on Computational Learning Theory (Santa Cruz, CA, USA, July\,31--Aug.\,2, 1989)}, year = 1990, pages = {134--145}, address = {San Francisco, CA, USA}, publisher = {Morgan Kaufmann}, isbn = {1-55860-086-8}, url = {http://portal.acm.org/citation.cfm?id=93351}, keywords = {induction; learnability; machine learning; pac-learning} }
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Yuichiro Anzai and Herbert A. Simon.
The theory of learning by doing.
Psychological Review, 86(2):124-140, 1979.
@article{anzai/simon:1979, author = {Yuichiro Anzai and Herbert A. Simon}, title = {The Theory of Learning by Doing}, journal = {Psychological Review}, year = 1979, volume = 86, number = 2, pages = {124--140}, publisher = {American Psychological Association}, keywords = {cognition} }
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Y. Anzai and Y. Uesato.
Learning recursive procedures by middleschool children.
In CogSci'82: Proceedings of the 4th Annual Conference of the
Cognitive Science Society, pages 100-102, 1982.
@inproceedings{anzai/uesato:1982, author = {Y. Anzai and Y. Uesato}, title = {Learning recursive procedures by middleschool children}, booktitle = {{CogSci'82}: Proceedings of the 4th Annual Conference of the Cognitive Science Society}, year = 1982, pages = {100--102} }
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Hiroki Arimura.
Learning acyclic first-order Horn sentences from entailment.
In Ming Li and Akira Maruoka, editors, Algorithmic Learning
Theory. 8th International Workshop, ALT'97, Sendai, Japan, Oct.6-8,
1997. Proceedings, volume 1316 of Lecture Notes in Computer Science,
pages 432-445, Berlin/Heidelberg, 1997. Springer.
@inproceedings{arimura:1997, author = {Hiroki Arimura}, title = {Learning acyclic first-order {Horn} sentences from entailment}, editor = {Ming Li and Akira Maruoka}, booktitle = {Algorithmic Learning Theory. 8th International Workshop, {ALT'97}, Sendai, Japan, Oct.\,6--8, 1997. Proceedings}, year = 1997, series = {Lecture Notes in Computer Science}, volume = 1316, pages = {432--445}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-63577-2}, url = {http://www.springerlink.com/content/b3161327v1370748/}, doi = {10.1007/3-540-63577-7_59}, abstract = {This paper considers the problem of learning an unknown first-order Horn sentenceH*from examples of Horn clauses thatH*either implies or does not imply. Particularly, we deal with a subclass of first-order Horn sentencesACH(k), calledacyclic constrained Horn programs of constant arity k.ACH(k) allows recursions, disjunctive definitions, and the use of function symbols. We present an algorithm that exactly identifies every target Horn programH*in ACH(k) in polynomial time inp,mandnusingO(pmnk+1) entailment equivalence queries andO(pm2n2) request for hint queries, wherepis the number of predicates,mis the number of clauses contained inH*andnis the size of the longest counterexample. This algorithm combines saturation and least general generalization operators to invert resolution steps. Next, using the technique of replacing request for hint queries with entailment membership queries, we have a polynomial time learning algorithm using entailment equivalence and entailment membership queries for a subclass ofACH(k). Finally, we show that any algorithm which learnsACH(k) using entailment equivalence and entailment membership queries makes((mnk) queries, and that the use of entailment cannot be eliminated to learnACH(k) even with both equivalence and membership queries for ground atoms are allowed.} }
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A. Armando, A. Smaill, and I. Green.
Automatic synthesis of recursive programs: the proof-planning
paradigm.
In ASE'97: Proceedings of the 12th IEEE Conference on
Automated Software Engineering (Lake Tahoe, Nevada, Nov.2-5, 1997), pages
2-9, 1997.
@inproceedings{armando_ea:1997, author = {A. Armando and A. Smaill and I. Green}, title = {Automatic synthesis of recursive programs: the proof-planning paradigm}, booktitle = {{ASE'97}: Proceedings of the 12th {IEEE} Conference on Automated Software Engineering (Lake Tahoe, Nevada, Nov.\,2--5, 1997)}, year = 1997, pages = {2--9}, url = {http://dx.doi.org/10.1109/ASE.1997.632818}, isbn = {0-8186-7961-1}, keywords = {deductive program synthesis; inproceedings; program synthesis; proof-planning}, abstract = {We describe a proof plan that characterises a family of proofs corresponding to the synthesis of recursive functional programs. This plan provides a significant degree of automation in the construction of recursive programs from specifications, together with correctness proofs. This plan makes use of meta-variables to allow successive refinement of the identity of unknowns, and so allows the program and the proof to be developed hand in hand. We illustrate the plan with parts of a substantial example-the synthesis of a unification algorithm.} }
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Lennart Augustsson.
Announcing djinn, version 2004-12-11, a coding wizard, 2005.
@misc{augustsson:2005, author = {Lennart Augustsson}, title = {Announcing Djinn, version 2004-12-11, a coding wizard}, year = 2005, url = {http://permalink.gmane.org/gmane.comp.lang.haskell.general/12747} }
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Franz Baader and Tobias Nipkow.
Term Rewriting and All That.
Cambridge University Press, 1998.
@book{baader/nipkow:1998, author = {Franz Baader and Tobias Nipkow}, title = {Term Rewriting and All That}, publisher = {Cambridge University Press}, year = 1998, url = {http://www.cambridge.org/us/catalogue/catalogue.asp?isbn=9780521779203}, keywords = {book; equational logic; term rewriting; universal algebra}, annote = {the first comprehensive text book on term rewriting}, isbn = 0521779200 }
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Y. M. Barzdin', A. N. Brazma, and E. B. Kinber.
Inductive synthesis of programs: State of the art, problems,
prospects.
In Cybernetics and Systems Analysis, volume 23. Springer, 1988.
Formerly: Cybernetics. A Translation of Kibernetika i Sistemnyi
Analiz.
@incollection{barzdin_ea:1988, author = {Barzdin', Y. M. and Br{\=a}zma, A. N. and Kinber, E. B.}, title = {Inductive Synthesis of Programs: State of the Art, Problems, Prospects}, booktitle = {Cybernetics and Systems Analysis}, publisher = {Springer}, year = 1988, volume = 23, note = {Formerly: Cybernetics. A Translation of Kibernetika i Sistemnyi Analiz} }
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J. M. Barzdinš and U. Sarkans.
Incorporating hypothetical knowledge into the process of inductive
synthesis.
In S. Arikawa and A. K. Sharma, editors, Algorithmic Learning
Theory. 7th International Workshop, ALT'96, Sydney, Australia,
Oct.23-25, 1996. Proceedings, volume 1160 of Lecture Notes in
Computer Science, pages 156-168, Berlin/Heidelberg, 1996. Springer.
@inproceedings{barzdins/sarkans:1996, author = {B{\=a}rzdi{\c{n}}{\v{s}}, J. M. and Sarkans, U.}, title = {Incorporating hypothetical knowledge into the process of inductive synthesis}, editor = {S. Arikawa and A. K. Sharma}, booktitle = {Algorithmic Learning Theory. 7th International Workshop, {ALT'96}, Sydney, Australia, Oct.\,23--25, 1996. Proceedings}, year = 1996, series = {Lecture Notes in Computer Science}, volume = 1160, pages = {156--168}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-61863-8}, url = {http://www.springerlink.com/content/f8l18p3451426727/}, abstract = {The problem of inductive inference of functions from hypothetical knowledge is investigated in this paper. This type of inductive inference could be regarded as a generalization of synthesis from examples that can be directed not only by input/output examples but also by knowledge of, e. g., functional description's syntactic structure or assumptions about the process of function evaluation. We show that synthesis of this kind is possible by efficiently enumerating the hypothesis space and illustrate it with several examples.}, doi = {10.1007/3-540-61863-5_43}, annote = {ute-inflit} }
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J. M. Barzdinš, A. N. Brazma, and E. B. Kinber.
Models of inductive syntactical synthesis.
In Machine Intelligence, volume 12, pages 139-148. Oxford
University Press, 1990.
@incollection{barzdins_ea:1990, author = {B{\=a}rzdi{\c{n}}{\v{s}}, J. M. and Br{\=a}zma, A. N. and Kinber, E. B.}, title = {Models of inductive syntactical synthesis}, booktitle = {Machine Intelligence}, publisher = {Oxford University Press}, year = 1990, volume = 12, pages = {139--148} }
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J. M. Barzdinš, G. Barzdinš, K. Apsitis,
and U. Sarkans.
Towards efficient inductive synthesis of expressions from
input/output examples.
In K. P. Jandtke, S. Kobayashi, E. Tomita, and T. Yokomori, editors,
Algorithmic Learning Theory. 4th International Workshop on Analogical
and Inductive Inference, AII '94 5th International Workshop on Algorithmic
Learning Theory, ALT'94, Reinhardsbrunn Castle, Germany Oct.10-15, 1994.
Proceedings, volume 872 of Lecture Notes in Computer Science, pages
59-72, Berlin/Heidelberg, 1994. Springer.
@inproceedings{barzdins_ea:1994, author = {B{\=a}rzdi{\c{n}}{\v{s}}, J. M. and B{\=a}rzdi{\c{n}}{\v{s}}, G. and Aps{\=\i}tis, K. and Sarkans, U.}, title = {Towards efficient inductive synthesis of expressions from input/output examples}, editor = {K. P. Jandtke and S. Kobayashi and E. Tomita and T. Yokomori}, booktitle = {Algorithmic Learning Theory. 4th International Workshop on Analogical and Inductive Inference, AII '94 5th International Workshop on Algorithmic Learning Theory, {ALT'94}, Reinhardsbrunn Castle, Germany Oct.\,10--15, 1994. Proceedings}, year = 1994, series = {Lecture Notes in Computer Science}, volume = 872, pages = {59--72}, address = { Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-58520-6}, url = {http://www.springerlink.com/content/f2h1q3661h76t808/}, doi = {10.1007/3-540-58520-6_46}, annote = {ute-inflit} }
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Michael A. Bauer.
Programming by examples.
Artificial Intelligence, 12:1-21, 1979.
@article{bauer:1979, author = {Michael A. Bauer}, title = {Programming by examples}, journal = {Artificial Intelligence}, year = 1979, volume = 12, pages = {1--21} }
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Kent Beck.
Test-Driven Development By Example.
Addison-Wesley, 2003.
@book{beck:2003, author = {Kent Beck}, title = {Test-Driven Development By Example}, publisher = {Addison-Wesley}, year = 2003, keywords = {tdd} }
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Christoph Beierle.
Synthesizing minimal programs from traces of observable behavior.
Technical Report SEKI-BN-81-06, SEKI, Institut für Informatik,
Universität Bonn, 1981.
@techreport{beierle:1981, author = {Christoph Beierle}, title = {Synthesizing minimal programs from traces of observable behavior}, institution = {SEKI}, year = 1981, number = {SEKI-BN-81-06}, address = {Institut f\"ur Informatik, Universit\"at Bonn}, annote = {ute-inflit} }
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Margherita Berardi and Donato Malerba.
Learning recursive patterns for biomedical information extraction.
In Stephen H. Muggleton, Ramón P. Otero, and Alireza
Tamaddoni-Nezhad, editors, Inductive Logic Programming. 16th
International Conference, ILP'06, Santiago de Compostela, Spain,
Aug.24-27, 2006. Revised Selected Papers, volume 4455 of Lecture
Notes in Computer Science, pages 79-93, Berlin/Heidelberg, 2007.
Springer.
@inproceedings{berardi/malerba:2007, author = {Margherita Berardi and Donato Malerba}, title = {Learning Recursive Patterns for Biomedical Information Extraction}, editor = {Stephen H. Muggleton and Ram{\'o}n P. Otero and Alireza Tamaddoni-Nezhad}, booktitle = {Inductive Logic Programming. 16th International Conference, {ILP'06}, Santiago de Compostela, Spain, Aug.\,24--27, 2006. Revised Selected Papers}, year = 2007, series = {Lecture Notes in Computer Science}, volume = 4455, pages = {79--93}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-73846-6}, url = {http://www.springerlink.com/content/lw431m8668nu0887/}, abstract = {Information in text form remains a greatly unexploited source of biological information. Information Extraction (IE) techniques are necessary to map this information into structured representations that allow facts relating domain-relevant entities to be automatically recognized. In biomedical IE tasks, extracting patterns that model implicit relations among entities is particularly important since biological systems intrinsically involve interactions among several entities. In this paper, we resort to an Inductive Logic Programming (ILP) approach for the discovery of mutual recursive patterns from text. Mutual recursion allows dependencies among entities to be explored in data and extraction models to be applied in a context-sensitive mode. In particular, IE models are discovered in form of classification rules encoding the conditions to fill a pre-defined information template. An application to a real-world dataset composed by publications selected to support biologists in the task of automatic annotation of a genomic database is reported.}, doi = {10.1007/978-3-540-73847-3_15} }
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Margherita Berardi, Michelangelo Ceci, Floriana Esposito, and Donato Malerba.
Learning logic programs for layout analysis correction.
In Nina Mishra Tom Fawcett, editor, ICML'03: Proceedings of
the Twentieth International Conference on Machine Learning (Washington D.C.,
USA, Aug. 21-24, 2003), pages 27-34. AAAI Press, 2003.
@inproceedings{berardi_ea:2003, author = {Margherita Berardi and Michelangelo Ceci and Floriana Esposito and Donato Malerba}, title = {Learning Logic Programs for Layout Analysis Correction}, editor = {Tom Fawcett, Nina Mishra}, booktitle = {{ICML'03}: Proceedings of the Twentieth International Conference on Machine Learning (Washington D.C., USA, Aug.\, 21--24, 2003)}, year = 2003, pages = {27--34}, publisher = {AAAI Press}, isbn = {1-57735-189-4} }
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Margherita Berardi, Antonio Varlaro, and Donato Malerba.
On the effect of caching in recursive theory learning.
In Rui Camacho, Ross D. King, and Ashwin Srinivasan, editors,
Inductive Logic Programming. 14th International Conference, ILP'04, Porto,
Portugal, Sept.6-8, 2004. Proceedings, volume 3194 of Lecture Notes
in Computer Science, pages 83-90, Berlin/Heidelberg, 2004. Springer.
@inproceedings{berardi_ea:2004, author = {Margherita Berardi and Antonio Varlaro and Donato Malerba}, title = {On the Effect of Caching in Recursive Theory Learning}, editor = {Rui Camacho and Ross D. King and Ashwin Srinivasan}, booktitle = {Inductive Logic Programming. 14th International Conference, {ILP'04}, Porto, Portugal, Sept.\,6--8, 2004. Proceedings}, year = 2004, series = {Lecture Notes in Computer Science}, volume = 3194, pages = {83--90}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-22941-4}, url = {http://springerlink.metapress.com/content/pvyexctkth2c18ny/}, abstract = {This paper focuses on inductive learning of recursive logical theories from a set of examples. This is a complex task where the learning of one predicate definition should be interleaved with the learning of the other ones in order to discover predicate dependencies. To overcome this problem we propose a variant of the separate-and-conquer strategy based on parallel learning of different predicate definitions. In order to improve its efficiency, optimization techniques are investigated and adopted solutions are described. In particular, two caching strategies have been implemented and tested on document processing datasets. Experimental results are discussed and conclusions are drawn.}, doi = {10.1007/978-3-540-30109-7_8} }
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Henrik Berg, Roland J. Olsson, Per-Olav Rusås, and Morgan Jakobsen.
Synthesis of control algorithms for autonomous vehicles through
automatic programming.
In Haiying Wang, Kay Soon Low, Kexin Wei, and Junqing Sun, editors,
ICNC'09: Proceedings of the 5th International Conference on Natural
Computation (Tianjin, China, Aug.14-16, 2009), pages 445-453. IEEE
Computer Society, 2009.
@inproceedings{berg_ea:2009, author = {Henrik Berg and Roland J. Olsson and Per-Olav Rus{\aa}s and Morgan Jakobsen}, title = {Synthesis of Control Algorithms for Autonomous Vehicles through Automatic Programming}, editor = {Haiying Wang and Kay Soon Low and Kexin Wei and Junqing Sun}, booktitle = {{ICNC'09}: Proceedings of the 5th International Conference on Natural Computation (Tianjin, China, Aug.\,14--16, 2009)}, year = 2009, pages = {445--453}, publisher = {IEEE Computer Society}, keywords = {adate; inductive programming} }
-
Francesco Bergadano and Daniele Gunetti.
An interactive system to learn functional logic programs.
In Ruzena Bajcsy, editor, IJCAI'93: Proceedings of the 13th
International Joint Conference on Artificial Intelligence (Chambéry,
France, Aug.28-Sep.3, 1993). Morgan Kaufmann, 1993.
@inproceedings{bergadano/gunetti:1993, author = {Bergadano, Francesco and Gunetti, Daniele}, title = {An Interactive System to Learn Functional Logic Programs}, editor = {Ruzena Bajcsy}, booktitle = {{IJCAI'93}: Proceedings of the 13th International Joint Conference on Artificial Intelligence (Chamb\'ery, France, Aug.\,28--Sep.\,3, 1993)}, year = 1993, publisher = {Morgan Kaufmann}, keywords = {FILP; iflp; ilp; inductive programming; ip-system; program synthesis; recursion} }
-
Francesco Bergadano and Daniele Gunetti.
Inductive Logic Programming: From Machine Learning to Software
Engineering.
MIT Press, Cambridge, MA, USA, 1995.
@book{bergadano/gunetti:1995, author = {Bergadano, Francesco and Gunetti, Daniele}, title = {Inductive Logic Programming: From Machine Learning to Software Engineering}, publisher = {MIT Press}, year = 1995, address = {Cambridge, MA, USA}, keywords = {book; filp; ilp; induction; inductive programming; machine learning; program synthesis; software engineering}, isbn = 0262023938, url = {http://portal.acm.org/citation.cfm?id=546596#} }
-
W. Bibel and A. W. Biermann.
Special issue: Automatic programming, foreword of the guest editors.
Journal of Symbolic Computation, 15(5, 6):463-465, 1993.
@article{bibel/biermann:1993, author = {W. Bibel and A. W. Biermann}, title = {Special Issue: Automatic Programming, foreword of the guest editors}, journal = {Journal of Symbolic Computation}, year = 1993, volume = 15, number = {5, 6}, pages = {463--465} }
-
W. Bibel.
Syntax-directed, semantic-supported program synthesis.
Artificial Intelligence, 14(3):243-261, 1980.
@article{bibel:1980, author = {W. Bibel}, title = {Syntax-directed, semantic-supported program synthesis}, journal = {Artificial Intelligence}, year = 1980, volume = 14, number = 3, pages = {243--261} }
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W. Bibel, D. Korn, C. Kreitz, and F. Kurucz.
A multi-level approach to program synthesis.
In Norbert E. Fuchs, editor, Logic Programming Synthesis and
Transformation. 7th International Workshop, LOPSTR'97, Leuven, Belgium,
July10-12, 1997. Proceedings, volume 1207 of Lecture Notes in
Computer Science, pages 1-27, Berlin/Heidelberg, 1998. Springer.
@inproceedings{bibel_ea:1998, author = {W. Bibel and D. Korn and C. Kreitz and F. Kurucz}, title = {A Multi-level Approach to Program Synthesis}, editor = {Norbert E. Fuchs}, booktitle = {Logic Programming Synthesis and Transformation. 7th International Workshop, {LOPSTR'97}, Leuven, Belgium, July\,10--12, 1997. Proceedings}, year = 1998, series = {Lecture Notes in Computer Science}, volume = 1207, pages = {1--27}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, doi = {10.1007/3-540-49674-2_1}, url = {http://www.springerlink.com/content/d4ud8wf2gkpcll2q/}, abstract = {We present an approach to a coherent program synthesis system which integrates a variety of interactively controlled and automated techniques from theorem proving and algorithm design at different levels of abstraction. Besides providing an overall view we summarize the individual research results achieved in the course of this development.}, isbn = {978-3-540-65074-4} }
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Alan W. Biermann and Gerard Guiho, editors.
Computer Program Synthesis Methodologies.
Reidel, 1983.
@book{biermann/guiho:1983, editor = {Alan W. Biermann and Gerard Guiho}, title = {Computer Program Synthesis Methodologies}, publisher = {Reidel}, year = 1983 }
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Alan W. Biermann and R. Krishnaswamy.
Constructing programs from example computations.
IEEE Transactions on Software Engineering, 2(3):141-153, 1976.
@article{biermann/krishnaswamy:1976, author = {Alan W. Biermann and R. Krishnaswamy}, title = {Constructing Programs from Example Computations}, journal = {IEEE Transactions on Software Engineering}, year = 1976, volume = 2, number = 3, pages = {141--153}, address = {Los Alamitos, CA, USA}, publisher = {IEEE Computer Society}, keywords = {ase; induction; inductive programming; pre-summers; program synthesis; synthesis from traces}, url = {http://doi.ieeecomputersociety.org/10.1109/TSE.1976.233812}, abstract = {An autoprogrammer is an interactive computer programming system which automatically constructs computer programs from example computations executed by the user. The example calculations are done in a scratch pad fashion at a computer display using a light pen or other graphic input device, and the system stores a detailed history of all of the steps executed in the process. Then the system automatically synthesizes the shortest possible program which is capable of executing the observed examples. The paper describes the computational environment provided by the system, proves that the program synthesis technique is both "sound" and "complete," describes the design of the system, and gives some programs it was used to create.} }
-
Alan W. Biermann and Douglas R. Smith.
The hierarchical synthesis of LISP scanning programs.
In B. Gilchrist, editor, Information Processing 77, pages
41-45, Amsterdam, 1977. North-Holland Publishing.
@inproceedings{biermann/smith:1977, author = {Biermann, Alan W. and Smith, Douglas R.}, title = {The Hierarchical Synthesis of {LISP} Scanning Programs}, editor = {B. Gilchrist}, booktitle = {Information Processing 77}, year = 1977, pages = {41--45}, address = {Amsterdam}, publisher = {North-Holland Publishing}, keywords = {analytical ip; ifp; induction; inductive programming; program synthesis}, annote = {Surveyed, amongst others, in Smith, The Synthesis of LISP programs from Examples: A Survey, 1984.} }
-
Alan W. Biermann and Douglas R. Smith.
A production rule mechanism for generating LISP code.
IEEE Transactions on Systems, Man, and Cybernetics,
9(5):260-276, 1979.
@article{biermann/smith:1979, author = {Biermann, Alan W. and Smith, Douglas R.}, title = {A Production Rule Mechanism for Generating {LISP} Code}, journal = {IEEE Transactions on Systems, Man, and Cybernetics}, year = 1979, volume = 9, number = 5, pages = {260--276}, url = {http://ieeexplore.ieee.org/Xplore/login.jsp?url=/iel5/21/4310191/04310195.pdf?arnumber=4310195}, keywords = {analytical ip; ifp; induction; inductive programming; program synthesis}, annote = {Surveyed in Smith, The Synthesis of LISP programs from Examples: A Survey, 1984}, abstract = {Production rule schemas are given which hold the basic information necessary for coding recursive loops and branches in LISP. Information from the user concerning the desired program is used to instantiate the schemas to yield production rules, and then these rules generate executable code in a strictly syntactic fashion. Emphasis is placed on decomposing the synthesis problem into a hierarchy of tasks which can each be solved by application of a schema. The method is demonstrated by showing how programs can be synthesized from examples of their input-output behaviors.} }
-
Alan W. Biermann.
On the inference of Turing machines from sample computations.
Artificial Intelligence, 3(3):181-198, 1972.
@article{biermann:1972, author = {Biermann, Alan W.}, title = {On the inference of {Turing} machines from sample computations}, journal = {Artificial Intelligence}, year = 1972, volume = 3, number = 3, pages = {181--198} }
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Alan W. Biermann.
The inference of regular LISP programs from examples.
IEEE Transactions on Systems, Man and Cybernetics,
8(8):585-600, 1978.
@article{biermann:1978, author = {Biermann, Alan W.}, title = {The Inference of Regular {LISP} Programs from Examples}, journal = {IEEE Transactions on Systems, Man and Cybernetics}, year = 1978, volume = 8, number = 8, pages = {585--600}, url = {http://ieeexplore.ieee.org/Xplore/login.jsp?url=/iel5/21/4310032/04310035.pdf?arnumber=4310035}, keywords = {analytical ip; ifp; induction; inductive programming; program synthesis; synthesis from traces}, annote = {Surveyed in Smith, The Synthesis of LISP Programs from Examples: A Survey, 1984}, abstract = {A class of LISP programs that is analogous to the finite-state automata is defined, and an algorithm is given for constructing such programs from examples of their input-output behavior. It is shown that the algorithm has robust performance for a wide variety of inputs and that it converges to a solution on the basis of minimum input information. } }
-
Alan W. Biermann.
Dealing with search.
In Alan W. Biermann, Yves Kodratoff, and Gerard Guiho, editors,
Automatic Program Construction Techniques, chapter 17, pages 375-392. The
Free Press, New York, NY, USA, 1984.
@incollection{biermann:1984, author = {Biermann, Alan W.}, title = {Dealing With Search}, editor = {Alan W. Biermann and Yves Kodratoff and Gerard Guiho}, booktitle = {Automatic Program Construction Techniques}, publisher = {The Free Press}, year = 1984, chapter = 17, pages = {375--392}, address = {New York, NY, USA}, isbn = 0029490707, keywords = {analytical ip; enumerative ip; ifp; induction; inductive programming; lisp; program synthesis}, annote = {overview over the synthesis of regular and scanning LISP programs} }
-
Alan W. Biermann.
Automatic programming: a tutorial on formal methodologies.
Journal of Symbolic Compututation, 1(2):119-142, 1985.
@article{biermann:1985, author = {Biermann, Alan W.}, title = {Automatic Programming: a Tutorial on Formal Methodologies}, journal = {Journal of Symbolic Compututation}, year = 1985, volume = 1, number = 2, pages = {119--142}, address = {Duluth, MN, USA}, publisher = {Academic Press}, keywords = {analytical ip; ase; deductive program synthesis; enumerative ip; ifp; induction; inductive programming; lisp; program synthesis}, annote = {overview of deductive, inductive, from natural language automatic programming methods}, url = {http://dx.doi.org/10.1016/S0747-7171(85)80010-9} }
-
Alan W. Biermann.
Automatic programming.
In Stuart C. Shapiro, editor, Encyclopedia of Artificial
Intelligence, pages 18-35. John Wiley & Sons, Inc., New York, NY, USA, 2
edition, 1992.
@incollection{biermann:1992, author = {Biermann, Alan W.}, title = {Automatic Programming}, editor = {Stuart C. Shapiro}, booktitle = {Encyclopedia of Artificial Intelligence}, publisher = {John Wiley \& Sons, Inc.}, year = 1992, pages = {18--35}, address = {New York, NY, USA}, edition = 2, keywords = {analytical ip; ase; deductive program synthesis; enumerative ip; formal methods; ifp; ilp; induction; inductive programming; lisp; overview; program synthesis}, annote = {overview of deductive, inductive, ilp, and from natural language automatic programming methods} }
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Alan W. Biermann, R. I. Baum, and F. E. Petry.
Speeding up the synthesis of programs from traces.
IEEE Transactions on Computers, 24(2):122-136, 1975.
@article{biermann_ea:1975, author = {Alan W. Biermann and R. I. Baum and F. E. Petry}, title = {Speeding up the Synthesis of Programs from Traces}, journal = {IEEE Transactions on Computers}, year = 1975, volume = 24, number = 2, pages = {122--136}, address = {Los Alamitos, CA, USA}, publisher = {IEEE Computer Society}, url = {http://doi.ieeecomputersociety.org/10.1109/T-C.1975.224180}, keywords = {analytical ip; enumerative ip; induction; inductive programming; program synthesis; synthesis from traces}, abstract = {An algorithm is given for synthesizing a computer program from a trace of its behavior. Since the algorithm involves a search, the length of time required to do the synthesis of nontrivial programs can be quite large. Techniques are given for preprocessing the trace information to reduce enumeration, for pruning the search using a failure memory technique, and for utilizing multiple traces to the best advantage. The results of numerous tests are given to demonstrate the value of the techniques.} }
-
Alan W. Biermann, Yves Kodratoff, and Gerard Guiho.
Automatic Program Construction Techniques.
The Free Press, New York, NY, USA, 1984.
@book{biermann_ea:1984, author = {Alan W. Biermann and Yves Kodratoff and Gerard Guiho}, title = {Automatic Program Construction Techniques}, publisher = {The Free Press}, year = 1984, address = {New York, NY, USA}, isbn = 0029490707 }
-
Franck Binard and Amy Felty.
An abstraction-based genetic programming system.
In Dirk Thierens, editor, GECCO'07: Proceedings of the 9th
Annual Conference on Genetic and Evolutionary Computation (London, England,
UK, July7-11, 2007). Companion Material, pages 2415-2422, New York, NY,
USA, 2007. ACM.
Session “Late-breaking papers”.
@inproceedings{binard/felty:2007, author = {Binard, Franck and Felty, Amy}, title = {An abstraction-based genetic programming system}, editor = {Dirk Thierens}, booktitle = {{GECCO'07}: Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation (London, England, UK, July\,7--11, 2007). Companion Material}, year = 2007, pages = {2415--2422}, address = {New York, NY, USA}, publisher = {{ACM}}, note = {Session ``Late-breaking papers''}, url = {http://doi.acm.org/10.1145/1274000.1274004}, isbn = {978-1-59593-698-1} }
-
Franck Binard and Amy Felty.
Genetic programming with polymorphic types and higher-order
functions.
In Conor Ryan and Maarten Keijzer, editors, GECCO'08:
Proceedings of the 10th Annual Conference on Genetic and Evolutionary
Computation (Atlanta, GA, USA, July12-16, 2008), pages 1187-1194, New
York, NY, USA, 2008. ACM.
Session “Genetic programming papers”.
@inproceedings{binard/felty:2008, author = {Franck Binard and Amy Felty}, title = {Genetic Programming with Polymorphic Types and Higher-Order Functions}, editor = {Conor Ryan and Maarten Keijzer}, booktitle = {{GECCO'08}: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation (Atlanta, GA, USA, July\,12--16, 2008)}, year = 2008, pages = {1187--1194}, address = {New York, NY, USA}, publisher = {{ACM}}, note = {Session ``Genetic programming papers''}, isbn = {978-1-60558-130-9}, url = {http://doi.acm.org/10.1145/1389095.1389330}, keywords = {enumerative ip; gp; higher-order functions; ifp; induction; inductive programming; program evolution; program synthesis} }
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Holger Bischof, Sergei Gorlatch, and Emanuel Kitzelmann.
The double-scan skeleton and its parallelization.
Technical report, Technische Universität Berlin, 2002.
@techreport{bischof_ea:2002, author = {Holger Bischof and Sergei Gorlatch and Emanuel Kitzelmann}, title = {The Double-Scan Skeleton and its Parallelization}, institution = {{Technische Universit{\"a}t Berlin}}, year = 2002, keywords = {parallel programming} }
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Holger Bischof, Sergei Gorlatch, and Emanuel Kitzelmann.
Cost optimality and predictability of parallel programming with
skeletons.
Parallel Processing Letters, 13(4):575-587, 2003.
@article{bischof_ea:2003, author = {Holger Bischof and Sergei Gorlatch and Emanuel Kitzelmann}, title = {Cost Optimality And Predictability Of Parallel Programming with Skeletons}, journal = {Parallel Processing Letters}, year = 2003, volume = 13, number = 4, pages = {575--587}, url = {http://dx.doi.org/10.1142/S0129626403001525}, keywords = {article; parallel programming; skeletons} }
-
Holger Bischof, Sergei Gorlatch, and Emanuel Kitzelmann.
Design and implementation of a cost-optimal parallel tridiagonal
system solver using skeletons.
In Parallel Computing Technologies, volume 2763 of Lecture
Notes in Computer Science, pages 415-428, Berlin/Heidelberg, 2003.
Springer.
@inproceedings{bischof_ea:2003b, author = {Holger Bischof and Sergei Gorlatch and Emanuel Kitzelmann}, title = {Design and Implementation of a Cost-Optimal Parallel Tridiagonal System Solver Using Skeletons}, booktitle = {Parallel Computing Technologies}, year = 2003, series = {Lecture Notes in Computer Science}, volume = 2763, pages = {415--428}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-40673-0}, url = {http://www.springerlink.com/content/j1362563434l61n6}, doi = {10.1007/978-3-540-45145-7_39}, keywords = {inproceedings; parallel programming; skeletons; tridiagonal system solver}, abstract = {We address the problem of systematically designing correct parallel programs and developing their efficient implementations on parallel machines. The design process starts with an intuitive, sequential algorithm and proceeds by expressing it in terms of well-defined, pre-implemented parallel components called skeletons. We demonstrate the skeleton-based design process using the tridiagonal system solver as our example application. We develop step by step three provably correct, parallel versions of our application, and finally arrive at a cost-optimal implementation in MPI (Message Passing Interface). The performance of our solutions is demonstrated experimentally on a Cray T3E machine.} }
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Holger Bischof, Sergei Gorlatch, and Emanuel Kitzelmann.
Cost optimality and predictability of parallel programming with
skeletons.
In Euro-Par 2003 Parallel Processing. 9th International
Euro-Par Conference, Klagenfurt, Austria, Aug.26-29, 2003. Proceedings,
volume 2790 of Lecture Notes in Computer Science, pages 682-693,
Berlin/Heidelberg, 2004. Springer.
@inproceedings{bischof_ea:2004, author = {Holger Bischof and Sergei Gorlatch and Emanuel Kitzelmann}, title = {Cost Optimality and Predictability of Parallel Programming with Skeletons}, booktitle = {{Euro-Par 2003 Parallel Processing}. 9th International Euro-Par Conference, Klagenfurt, Austria, Aug.\,26--29, 2003. Proceedings}, year = 2004, series = {Lecture Notes in Computer Science}, volume = 2790, pages = {682--693}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, keywords = {inproceedings; parallel programming; skeletons}, abstract = {Skeletons are reusable, parameterized components with well-defined semantics and pre-packaged efficient parallel implementation. This paper develops a new, provably cost-optimal implementation of the DS (double-scan) skeleton for the divide-and-conquer paradigm. Our implementation is based on a novel data structure called plist (pointed list); implementation's performance is estimated using an analytical model. We demonstrate the use of the DS skeleton for parallelizing a tridiagonal system solver and report experimental results for its MPI implementation on a Cray T3E and a Linux cluster: they confirm the performance improvement achieved by the cost-optimal implementation and demonstrate its good predictability by our performance model.}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-40788-1}, url = {http://www.springerlink.com/content/602ycb05htd85f24}, doi = {10.1007/978-3-540-45209-6_97} }
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Henrik Boström.
Specialization of recursive predicates.
In Nada Lavrac and Stefan Wrobel, editors, Machine Learning:
ECML-95. 8th European Conference on Machine Learning Heraclion, Crete,
Greece, April25-27, 1995. Proceedings, volume 912 of Lecture Notes
in Computer Science, pages 92-106, Berlin/Heidelberg, 1995. Springer.
@inproceedings{bostroem:1995, author = {Henrik Bostr\"{o}m}, title = {Specialization of Recursive Predicates}, editor = {Nada Lavrac and Stefan Wrobel}, booktitle = {Machine Learning: {ECML-95}. 8th European Conference on Machine Learning Heraclion, Crete, Greece, April\,25--27, 1995. Proceedings}, year = 1995, series = {Lecture Notes in Computer Science}, volume = 912, pages = {92--106}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-59286-0}, url = {http://www.springerlink.com/content/f463100m0744736q/}, doi = {10.1007/3-540-59286-5_51}, keywords = {SPECTRE; ilp; inductive programming; ip-system; program synthesis; recursion}, abstract = {When specializing a recursive predicate in order to exclude a set of negative examples without excluding a set of positive examples, it may not be possible to specialize or remove any of the clauses in a refutation of a negative example without excluding any positive examples. A previously proposed solution to this problem is to apply program transformation in order to obtain non-recursive target predicates from recursive ones. However, the application of this method prevents recursive specializations from being found. In this work, we present the algorithm SPECTRE II which is not limited to specializing non-recursive predicates. The key idea upon which the algorithm is based is that it is not enough to specialize or remove clauses in refutations of negative examples in order to obtain correct specializations, but it is sometimes necessary to specialize clauses that appear only in refutations of positive examples. In contrast to its predecessor SPECTRE, the new algorithm is not limited to specializing clauses defining one predicate only, but may specialize clauses defining multiple predicates. Furthermore, the positive and negative examples are no longer required to be instances of the same predicate. It is proven that the algorithm produces a correct specialization when all positive examples are logical consequences of the original program, there is a finite number of derivations of positive and negative examples and when no positive and negative examples have the same sequence of input clauses in their refutations.} }
-
H. Boström.
Theory-guided induction of logic programs by inference of regular
languages.
In Lorenza Saitta, editor, ICML '96: Proceedings of the
Thirteenth International Conference on Machine Learning (Bari, Italy,
July3-6, 1996), pages 46-53. Morgan Kaufmann, 1996.
@inproceedings{bostroem:1996, author = {H. Bostr{\"o}m}, title = {Theory-guided induction of logic programs by inference of regular languages}, editor = {Lorenza Saitta}, booktitle = {{ICML '96}: Proceedings of the Thirteenth International Conference on Machine Learning (Bari, Italy, July\,3--6, 1996)}, year = 1996, pages = {46--53}, publisher = {Morgan Kaufmann}, isbn = {1-55860-419-7} }
-
H. Boström.
Predicate invention and learning from positive examples only.
In Claire Nedellec and Céline Rouveirol, editors, Machine
Learning: ECML-98. 10th European Conference on Machine Learning, Chemnitz,
Germany, April21-23, 1998. Proceedings, volume 1398 of Lecture Notes
in Computer Science, pages 226-237, Berlin/Heidelberg, 1998. Springer.
@inproceedings{bostroem:1998, author = {H. Bostr{\"o}m}, title = {Predicate Invention and Learning from Positive Examples Only}, editor = {Claire Nedellec and C{\'e}line Rouveirol}, booktitle = {Machine Learning: {ECML-98}. 10th European Conference on Machine Learning, Chemnitz, Germany, April\,21--23, 1998. Proceedings}, year = 1998, series = {Lecture Notes in Computer Science}, volume = 1398, pages = {226--237}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-64417-0}, url = {http://www.springerlink.com/content/5h0440715vx65g71/}, abstract = {Previous bias shift approaches to predicate invention are not applicable to learning from positive examples only, if a complete hypothesis can be found in the given language, as negative examples are required to determine whether new predicates should be invented or not. One approach to this problem is presented, MERLIN 2.0, which is a successor of a system in which predicate invention is guided by sequences of input clauses in SLD-refutations of positive and negative examples w.r.t. an overly general theory. In contrast to its predecessor which searches for the minimal finite-state automaton that can generate all positive and no negative sequences, MERLIN 2.0 uses a technique for inducing Hidden Markov Models from positive sequences only. This enables the system to invent new predicates without being triggered by negative examples. Another advantage of using this induction technique is that it allows for incremental learning. Experimental results are presented comparing MERLIN 2.0 with the positive only learning framework of Progol 4.2 and comparing the original induction technique with a new version that produces deterministic Hidden Markov Models. The results show that predicate invention may indeed be both necessary and possible when learning from positive examples only as well as it can be beneficial to keep the induced model deterministic.}, doi = {10.1007/BFb0026693} }
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H. Boström.
Induction of recursive transfer rules.
In Cussens J., editor, Learning Language in Logic, volume
1925 of Lecture Notes in Computer Science. Lecture Notes in Artificial
Intelligence, pages 369-450. Springer, Berlin/Heidelberg, 2000.
@incollection{bostroem:2000, author = {H. Bostr{\"o}m}, title = {Induction of Recursive Transfer Rules}, editor = {Cussens J.}, booktitle = {{Learning Language in Logic}}, publisher = {Springer}, year = 2000, volume = 1925, series = {Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence}, pages = {369--450}, address = {Berlin\,/\,Heidelberg}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-41145-1}, url = {http://www.springerlink.com/content/01pxw099u4u4cwxp/}, abstract = {Transfer rules are used in bi-lingual translation systems for transferring a logical representation of a source language sentence into a logical representation of the corresponding target language sentence. This work studies induction of transfer rules from examples of corresponding pairs of source-target quasi logical formulae (QLFs). The main features of this problem are: i) more than one rule may need to be produced from a single example, ii) only positive examples are provided and iii) the produced hypothesis should be recursive. In an earlier study of this problem, a system was proposed in which hand-coded heuristics were employed for identifying non-recursive correspondences. In this work we study the case when non-recursive transfer rules have been given to the system instead of heuristics. Results from a preliminary experiment with English-French QLFs are presented, demonstrating that this information is sufficient for the generation of generally applicable rules that can be used for transfer between previously unseen source and target QLFs. However, the experiment also shows that the system suffers from producing overly specific rules, even when the problem of disallowing the derivation of other target QLFs than the correct one is not considered. Potential approaches to this problem are discussed.}, doi = {10.1007/3-540-40030-3_15} }
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A. F. Bowers, C. Giraud-Carrier, C. Kennedy, J. W. Lloyd, and
R. MacKinney-Romero.
A framework for higher-order inductive machine learning.
In Peter A. Flach and Nada Lavrac, editors, Proceedings of the
CompulogNet Area Meeting on Representation issues in reasoning and learning
(CSTR-97-005, Department of Computer Science, University of Bristol.
Sept.20, 1997), 1997.
In conjunction with the Seventh International Workshop on Inductive
Logic Programming ILP'97.
@inproceedings{bowers_ea:1997, author = {A. F. Bowers and C. Giraud-Carrier and C. Kennedy and J. W. Lloyd and R. MacKinney-Romero}, title = {A Framework for Higher-Order Inductive Machine Learning}, editor = {Peter A. Flach and Nada Lavrac}, booktitle = {Proceedings of the {CompulogNet} Area Meeting on Representation issues in reasoning and learning ({CSTR-97-005}, Department of Computer Science, University of Bristol. Sept.\,20, 1997)}, year = 1997, note = {In conjunction with the Seventh International Workshop on Inductive Logic Programming {ILP'97}} }
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Robert S. Boyer and J. Strother Moore.
Proving theorems about LISP functions.
Journal of the ACM, 22(1):129-144, January 1975.
@article{boyer/moore:1975, author = {Boyer, Robert S. and Moore, J. Strother}, title = {Proving Theorems about {LISP} Functions}, journal = {Journal of the {ACM}}, year = 1975, volume = 22, number = 1, pages = {129--144}, month = {January}, address = {New York, NY, USA}, annote = {The BMWk algo of Kodratoff et al is named based on this paper.}, publisher = {{ACM}}, keywords = {lisp; theorem proving}, url = {http://doi.acm.org/10.1145/321864.321875}, abstract = {Program verification is the idea that properties of programs can be precisely stated and proved in the mathematical sense. In this paper, some simple heuristics combining evaluation and mathematical induction are described, which the authors have implemented in a program that automatically proves a wide variety of theorems about recursive LISP functions. The method the program uses to generate induction formulas is described at length. The theorems proved by the program include that REVERSE is its own inverse and that a particular SORT program is correct. A list of theorems proved by the program is given.} }
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Ivan Bratko and Stephen H. Muggleton.
Applications of inductive logic programming.
Communications of the ACM, 38(11):65-70, 1995.
@article{bratko/muggleton:1995, author = {Ivan Bratko and Stephen H. Muggleton}, title = {Applications of Inductive Logic Programming}, journal = {Communications of the {ACM}}, year = 1995, volume = 38, number = 11, pages = {65--70}, keywords = {1995; applications; article; ilp; induction; inductive inference; survey}, doi = {http://doi.acm.org/10.1145/219717.219771}, abstract = {Techniques of machine learning have been successfully applied to various problems. Most of these applications rely on attribute-based learning, exemplified by the induction of decision trees as in the program C4.5. Broadly speaking, attribute-based learning also includes such approaches to learning as neural networks and nearest neighbor techniques. The advantages of attribute-based learning are: relative simplicity, efficiency, and existence of effective techniques for handling noisy data. However, attribute-based learning is limited to non-relational descriptions of objects in the sense that the learned descriptions do not specify relations among the objects' parts. Attribute-based learning thus has two strong limitations: the background knowledge can be expressed in rather limited form, and the lack of relations makes the concept description language inappropriate for some domains.} }
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Ivan Bratko.
Prolog Programming for Artificial Intelligence.
Addison-Wesley, 1986.
@book{bratko:1986, author = {Ivan Bratko}, title = {Prolog Programming for Artificial Intelligence}, publisher = {Addison-Wesley}, year = 1986, keywords = {prolog} }
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A Brazma and E. B. Kinber.
Generalized regular expressions - a language for synthesis of
programs with branching in loops.
Theoretical Computer Science, 46:175-195, 1986.
@article{brazma/kinber:1986, author = {Br{\=a}zma, A and Kinber, E. B.}, title = {Generalized regular expressions -- a language for synthesis of programs with branching in loops}, journal = {Theoretical Computer Science}, year = 1986, volume = 46, pages = {175--195}, publisher = {Elsevier Science Publishers Ltd.}, address = {Essex, UK} }
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A. Brazma.
Inductive synthesis of dot expressions.
In J. M. Barzdinš and D. Bjorner, editors,
Baltic Computer Science. Selected Papers, volume 502 of Lecture Notes
in Computer Science, pages 156-212. Springer, Berlin/Heidelberg, 1991.
@incollection{brazma:1991, author = {A. Br{\=a}zma}, title = {Inductive synthesis of dot expressions}, editor = {B{\=a}rzdi{\c{n}}{\v{s}}, J. M. and Bjorner, D.}, booktitle = {Baltic Computer Science. Selected Papers}, publisher = {Springer}, year = 1991, volume = 502, series = {Lecture Notes in Computer Science}, pages = {156--212}, address = {Berlin\,/\,Heidelberg}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-54131-8}, url = {http://www.springerlink.com/content/57332j2671j7p508/}, abstract = {We consider the problem of the synthesis of algorithms by sample computations. We introduce a formal language, namely, the so-called dot expressions, which is based on a formalization of the intuitive notion of ellipsis (......). Whilst formally the dot expressions are simply a language describing sets of words, on the other hand, it can be considered as a programming language supporting quite a wide class of programs. Equivalence and asymptotical equivalence of dot expressions are defined and proved to be decidable. A formal example of a dot expression is defined in the way that, actually, it represents a sample computation of the program presented by the given dot expression. A system of simple inductive inference rules synthesizing dot expressions (programs) by their formal examples (sample computations) is developed and proved to synthesize a correct (i.e., asymptotically equivalent to the given) expression by one sufficiently long example. Some instances of the application of the model for program inductive synthesis are also given. Particularly, there are given examples of the euclidean and bubblesort algorithm synthesis within acceptable time from completely natural sample descriptions.). Whilst formally the dot expressions are simply a language describing sets of words, on the other hand, it can be considered as a programming language supporting quite a wide class of programs. Equivalence and asymptotical equivalence of dot expressions are defined and proved to be decidable. A formal example of a dot expression is defined in the way that, actually, it represents a sample computation of the program presented by the given dot expression. A system of simple inductive inference rules synthesizing dot expressions (programs) by their formal examples (sample computations) is developed and proved to synthesize a correct (i.e., asymptotically equivalent to the given) expression by one sufficiently long example. Some instances of the application of the model for program inductive synthesis are also given. Particularly, there are given examples of the euclidean and bubblesort algorithm synthesis within acceptable time from completely natural sample descriptions.}, doi = {10.1007/BFb0019359} }
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R. M. Burstall and John Darlington.
A transformation system for developing recursive programs.
Journal of the ACM, 24(1):44-67, January 1977.
@article{burstall/darlington:1977, author = {R. M. Burstall and John Darlington}, title = {A Transformation System for Developing Recursive Programs}, journal = {Journal of the {ACM}}, year = 1977, volume = 24, number = 1, pages = {44--67}, month = {January}, address = {New York, NY, USA}, publisher = {{ACM}}, url = {http://doi.acm.org/10.1145/321992.321996}, keywords = {article; ase; deductive program synthesis; program optimisation; program synthesis; program transformation}, annote = {A Transformation System for Developing Recursive Programs}, abstract = {A system of rules for transforming programs is described, with the programs in the form of recursion equations. An initially very simple, lucid, and hopefully correct program is transformed into a more efficient one by altering the recursion structure. Illustrative examples of program transformations are given, and a tentative implementation is described. Alternative structures for programs are shown, and a possible initial phase for an automatic or semiautomatic program-manipulation system is indicated.} }
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C. T. P. Burton.
Program morphisms.
Formal Aspects of Computing, 4:693-726, 1992.
@article{burton:1992, author = {C. T. P. Burton}, title = {Program Morphisms}, journal = {Formal Aspects of Computing}, year = 1992, volume = 4, pages = {693--726}, keywords = {category; definition; functional; parallel; recursive; theory; transformation}, abstract = {An algebraic view of recursive definitions is presented, extending an already familiar analogy with homomorphisms. A notion of simulation of one recursive definition by another is then defined. This leads to a particular approach to verification and transformation, which places emphasis on the arrows between programs, rather than the programs themselves. These arrows are the program morphisms of the title. Examples are given, together with certain extensions of the idea. Also indicated is a methodology which can lead to the discovery of program morphisms and new equivalent versions of a given program.}, annote = {ute-inflit} }
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Rui Camacho, Ross D. King, and Ashwin Srinivasan, editors.
Inductive Logic Programming, 14th International Conference,
ILP'04, Porto, Portugal, Sept.6-8, 2004, Proceedings, volume 3194 of
Lecture Notes in Computer Science, Berlin/Heidelberg, 2004.
Springer.
@proceedings{camacho_ea:2004, title = {Inductive Logic Programming, 14th International Conference, {ILP'04}, Porto, Portugal, Sept.\,6--8, 2004, Proceedings}, year = 2004, editor = {Rui Camacho and Ross D. King and Ashwin Srinivasan}, volume = 3194, series = {Lecture Notes in Computer Science}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-22941-4}, url = {http://www.springerlink.com/content/j9u24yq8m52r/}, doi = {10.1007/b10011} }
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R. Mike Cameron-Jones and J. Ross Quinlan.
Avoiding pitfalls when learning recursive theories.
In Ruzena Bajcsy, editor, IJCAI'93: Proceedings of the 13th
International Joint Conference on Artificial Intelligence (Chambéry,
France, Aug.28-Sep.3, 1993), pages 1050-1057. Morgan Kaufmann, 1993.
@inproceedings{cameron-jones/quinlan:1993, author = {R. Mike Cameron-Jones and J. Ross Quinlan}, title = {Avoiding Pitfalls When Learning Recursive Theories}, editor = {Ruzena Bajcsy}, booktitle = {{IJCAI}'93: Proceedings of the 13th International Joint Conference on Artificial Intelligence (Chamb\'ery, France, Aug.\,28--Sep.\,3, 1993)}, year = 1993, pages = {1050--1057}, publisher = {Morgan Kaufmann}, annote = {foil, assuring termination for recursive theories}, documenturl = {http://www.rulequest.com/Personal/cj+q.ijcai93.ps}, keywords = {enumerative ip; foil; ilp; induction; inductive programming; inproceedings; machine learning; program synthesis} }
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R. Mike Cameron-Jones and J. Ross Quinlan.
Efficient top-down induction of logic programs.
SIGART Bulletin, 5(1):33-42, January 1994.
@article{cameron-jones/quinlan:1994, author = {R. Mike Cameron-Jones and J. Ross Quinlan}, title = {Efficient Top-Down Induction of Logic Programs}, journal = {SIGART Bulletin}, year = 1994, volume = 5, number = 1, pages = {33--42}, month = {January}, address = {New York, NY, USA}, publisher = {{ACM}}, url = {http://doi.acm.org/10.1145/181668.181676}, keywords = {applications; article; enumerative ip; foil; ilp; induction; inductive programming; machine learning; program synthesis}, annote = {foil in 1994}, abstract = {FOIL is a system for inducing function-free Horn clause definitions of relations from example and extensionally defined background relations. It demonstrates the successful application of a general to specific approach to clause induction using heuristically guided search. This paper describes the current version of FOIL, assesses its performance and notes areas for improvement. The successful application of similar methods in other systems is reviewed to demonstrate their general utility.} }
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Baudouin Le Charlier and Pierre Flener.
Specifications are necessarily informal or: Some more myths of formal
methods.
Journal of Systems and Software, 40(3):275-296, 1998.
@article{charlier/flener:1998, author = {Baudouin Le Charlier and Pierre Flener}, title = {Specifications are necessarily informal or: Some more myths of formal methods}, journal = {Journal of Systems and Software}, year = 1998, volume = 40, number = 3, pages = {275--296}, address = {New York, NY, USA}, publisher = {Elsevier Science Inc.}, url = {http://dx.doi.org/10.1016/S0164-1212(98)00172-1}, keywords = {article; ase; comparison; formal methods; position paper; program synthesis; software engineering} }
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H. D. Cheng and K. S. Fu.
Algorithm partition and parallel recognition of general context-free
languages using fixed-size VLSI architecture.
Pattern Recognition, 19(5):361-372, 1986.
@article{cheng/fu:1986, author = {H. D. Cheng and K. S. Fu}, title = {Algorithm Partition and Parallel Recognition of General Context-Free Languages Using Fixed-Size {VLSI} Architecture}, journal = {Pattern Recognition}, year = 1986, volume = 19, number = 5, pages = {361--372}, publisher = {Elsevier Science Inc.}, address = {New York, NY, USA}, keywords = {language; matematics} }
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V. Ciesielski and Xiang Li.
Experiments with explicit for-loops in genetic programming.
In CEC'04: Proceedings of the IEEE Congress on Evolutionary
Computation (Portland, Oregon June20-23, 2004), pages 494-501. IEEE
Press, 2004.
@inproceedings{ciesielski/li:2004, author = {V. Ciesielski and Xiang Li}, title = {Experiments with Explicit For-Loops in Genetic Programming}, booktitle = {{CEC'04}: Proceedings of the IEEE Congress on Evolutionary Computation (Portland, Oregon June\,20--23, 2004)}, year = 2004, pages = {494--501}, publisher = {IEEE Press}, url = {http://dx.doi.org/10.1109/CEC.2004.1330897}, keywords = {enumerative ip; experiment; gp; induction; inductive programming; loops; program evolution; program synthesis}, abstract = {Evolving programs with explicit loops presents major difficulties, primarily due to the massive increase in the size of the search space. Fitness evaluation becomes computationally expensive and a method for dealing with infinite loops must be implemented. We have investigated ways of dealing with these problems by the evolution of for-loops of increasing semantic complexity. We have chosen two problems - a modified Santa Fe ant problem and a sorting problem - which have natural looping constructs in their solution and a solution without loops is not possible unless the tree depth is very large. We have shown that by controlling the complexity of the loop structures it is possible to evolve smaller and more understandable programs for these problems.} }
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Manuel Clavel, Francisco Durán, Steven Eker, Patrick Lincoln, Narciso
Martí-Oliet, , José Meseguer, and Carolyn Talcott.
The maude 2.0 system.
In R. Nieuwenhuis, editor, Rewriting Techniques and
Applications. 14th International Conference, RTA'03, Valencia, Spain,
June9-11, 2003. Proceedings, volume 2706 of Lecture Notes in
Computer Science, pages 76-87, Berlin/Heidelberg, 2003. Springer.
@inproceedings{clavel_ea:2003, author = {Manuel Clavel and Francisco Dur\'{a}n and Steven Eker and Patrick Lincoln and Narciso Mart\'{i}-Oliet and and Jos\'{e} Meseguer and Carolyn Talcott}, title = {The Maude 2.0 System}, editor = {R. Nieuwenhuis}, booktitle = {Rewriting Techniques and Applications. 14th International Conference, {RTA'03}, Valencia, Spain, June\,9--11, 2003. Proceedings}, year = 2003, series = {Lecture Notes in Computer Science}, volume = 2706, pages = {76--87}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, keywords = {algebraic specification; programming; programming language; specification; term rewriting}, abstract = {This paper gives an overview of the Maude 2.0 system. We emphasize the full generality with which rewriting logic and membership equational logic are supported, operational semantics issues, the new built-in modules, the more general Full Maude modulealgebra, the new META-LEVEL module, the LTL model checker, and new implementation techniques yielding substantial performance improvements in rewritingmodulo. We also comment on Maude's formal tool environment and on applications.}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-40254-1}, url = {http://www.springerlink.com/content/w605166t047792j4/}, doi = {10.1007/3-540-44881-0_7} }
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William W. Cohen.
Pac-learning a restricted class of recursive logic programs.
In AAAI'93: Proceedings of the 11th National Conference on
Artificial Intelligence (Washington, DC, USA, July11-15, 1993), pages
86-92. The AAAI Press/The MIT Press, 1993.
@inproceedings{cohen:1993, author = {William W. Cohen}, title = {Pac-Learning a Restricted Class of Recursive Logic Programs}, booktitle = {{AAAI'93}: Proceedings of the 11th National Conference on Artificial Intelligence (Washington, DC, USA, July\,11--15, 1993)}, year = 1993, pages = {86--92}, publisher = {The AAAI Press\,/\,The MIT Press}, keywords = {FORCE2; ilp; inductive programming; ip-system; learnability; program synthesis; recursion} }
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William W. Cohen.
Pac-learning recursive logic programs: Negative results.
Journal of Artificial Intelligence Research, pages 541-573,
1995.
@article{cohen:1995, author = {William W. Cohen}, title = {Pac-Learning Recursive Logic Programs: Negative Results}, journal = {Journal of Artificial Intelligence Research}, year = 1995, pages = {541--573}, url = {http://www.jair.org/vol/vol2.html}, doi = {10.1613/jair.1917}, keywords = {ilp; induction; inductive programming; learnability; pac-learning; program synthesis}, abstract = {In a companion paper it was shown that the class of constant-depth determinate k-ary recursive clauses is efficiently learnable. In this paper we present negative results showing that any natural generalization of this class is hard to learn in Valiant's model of pac-learnability. In particular, we show that the following program classes are cryptographically hard to learn: programs with an unbounded number of constant-depth linear recursive clauses; programs with one constant-depth determinate clause containing an unbounded number of recursive calls; and programs with one linear recursive clause of constant locality. These results immediately imply the non-learnability of any more general class of programs. We also show that learning a constant-depth determinate program with either two linear recursive clauses or one linear recursive clause and one non-recursive clause is as hard as learning boolean DNF. Together with positive results from the companion paper, these negative results establish a boundary of efficient learnability for recursive function-free clauses.} }
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William W. Cohen.
Pac-learning recursive logic programs: Efficient algorithms.
Journal of Artificial Intelligence Research, 2:501-539, 1995.
@article{cohen:1995b, author = {William W. Cohen}, title = {Pac-Learning Recursive Logic Programs: Efficient Algorithms}, journal = {Journal of Artificial Intelligence Research}, year = 1995, volume = 2, pages = {501--539}, url = {http://www.jair.org/vol/vol2.html}, doi = {10.1613/jair.97}, keywords = {ilp; induction; inductive programming; learnability; pac-learning; program synthesis}, abstract = {We present algorithms that learn certain classes of function-free recursive logic programs in polynomial time from equivalence queries. In particular, we show that a single k-ary recursive constant-depth determinate clause is learnable. Two-clause programs consisting of one learnable recursive clause and one constant-depth determinate non-recursive clause are also learnable, if an additional ``basecase'' oracle is assumed. These results immediately imply the pac-learnability of these classes. Although these classes of learnable recursive programs are very constrained, it is shown in a companion paper that they are maximally general, in that generalizing either class in any natural way leads to a computationally difficult learning problem. Thus, taken together with its companion paper, this paper establishes a boundary of efficient learnability for recursive logic programs.} }
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Darrell Conklin and Ian H. Witten.
Complexity-based induction.
Machine Learning, 16(3):203-225, September 1994.
@article{conklin/witten:1994, author = {Darrell Conklin and Ian H. Witten}, title = {Complexity-based Induction}, journal = {Machine Learning}, year = 1994, volume = 16, number = 3, pages = {203--225}, month = {September}, abstract = {A central problem in inductive logic programming is theory evaluation. Without some sort of preference criterion, any two theories that explain a set of examples are equally acceptable. This paper presents a scheme for evaluating alternative inductive theories based on an objective preference criterion. It strives to extract maximal redundancy from examples, transforming structure into randomness. A major strength of the method is its application to learning problems where negative examples of concepts are scarce or unavailable. A new measure called model complexity is introduced, and its use is illustrated and compared with a proof complexity measure on relational learning tasks. The complementarity of model and proof complexity parallels that of model and proof-theoretic semantics. Model complexity, where applicable, seems to be an appropriate measure for evaluating inductive logic theories.}, publisher = {Springer}, address = {Netherlands}, issn = {0885-6125 (Print) 1573-0565 (Online)}, url = {http://www.springerlink.com/content/j8732046806714x4/}, doi = {10.1023/A:1022641209111}, keywords = {Inductive logic programming; data compression; minimum description length principle; model complexity; learning from positive–only examples; theory preference criterion} }
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Bruno Courcelle.
Infinite trees in normal form and recursive equations having a unique
solution.
Theory of Computing Systems, 13(1):131-180, December 1979.
@article{courcelle:1979, author = {Bruno Courcelle}, title = {Infinite Trees in Normal Form and Recursive Equations having a Unique Solution}, journal = {Theory of Computing Systems}, year = 1979, volume = 13, number = 1, pages = {131--180}, month = {December}, publisher = {Springer}, keywords = {recursive program schemes; semantics}, abstract = {A system of recursive equations isC-univocal if it has a unique solution modulo the equivalence associated with a classC of interpretations. This concept yields simplified proofs of equivalence of recursive program schemes and correctness criteria for the validity of certain program transformations, provided one has syntactic easily testable conditions forC-univocality. Such conditions are given for equational classes of interpretations.}, address = {New York}, issn = {1432-4350 (Print) 1433-0490 (Online)}, url = {http://www.springerlink.com/content/u46w366127154368/}, doi = {10.1007/BF01744293} }
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Bruno Courcelle.
Recursive applicative program schemes.
In Handbook of Theoretical Computer Science: Formal Models and
Semantics, volume B, chapter 9, pages 459-492. MIT Press, Cambridge, MA,
USA, 1990.
@incollection{courcelle:1990, author = {Bruno Courcelle}, title = {Recursive Applicative Program Schemes}, booktitle = {Handbook of Theoretical Computer Science: Formal Models and Semantics}, publisher = {MIT Press}, year = 1990, volume = {B}, chapter = 9, pages = {459--492}, address = {Cambridge, MA, USA}, url = {http://portal.acm.org/citation.cfm?id=114891.114900}, keywords = {recursive program schemes; semantics} }
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Michael A. Covington.
Natural Language Processing for Prolog Programmers.
Prentice Hall, Upper Saddle River, NJ, USA, 1993.
@book{covington:1993, author = {Michael A. Covington}, title = {Natural Language Processing for Prolog Programmers}, publisher = {Prentice Hall}, year = 1993, address = {Upper Saddle River, NJ, USA}, isbn = 0136292135, keywords = {nlp} }
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Neil Crossley, Emanuel Kitzelmann, Martin Hofmann, and Ute Schmid.
Combining analytical and evolutionary inductive programming.
In B. Goertzel, P. Hitzler, and M. Hutter, editors, Artificial
General Intelligence. AGI'09: Proceedings of the 2nd Conference on
Artificial General Intelligence (Arlington, Virginia, March6-9, 2009),
Advances in Intelligent Systems Research, pages 19-24. Atlantis Press, 2009.
@inproceedings{crossley_ea:2009, author = {Neil Crossley and Emanuel Kitzelmann and Martin Hofmann and Ute Schmid}, title = {Combining Analytical and Evolutionary Inductive Programming}, editor = {B. Goertzel and P. Hitzler and M. Hutter}, booktitle = {Artificial General Intelligence. {AGI'09}: Proceedings of the 2nd Conference on Artificial General Intelligence (Arlington, Virginia, March\,6--9, 2009)}, year = 2009, series = {Advances in Intelligent Systems Research}, pages = {19--24}, publisher = {Atlantis Press}, isbn = {978-90-78677-24-6}, url = {http://dx.doi.org/10.2991/agi.2009.1}, keywords = {inductive programming}, abstract = {Analytical inductive programming and evolutionary inductive programming are two opposing strategies for learning recursive programs from incomplete specifications such as input/output examples. Analytical inductive programming is data-driven, namely, the minimal recursive generalization over the positive input/output examples is generated by recurrence detection. Evolutionary inductive programming, on the other hand, is based on searching through hypothesis space for a (recursive) program which performs sufficiently well on the given input/output examples with respect to some measure of fitness. While analytical approaches are fast and guarantee some characteristics of the induced program by construction (such as minimality and termination) the class of inducable programs is restricted to problems which can be specified by few positive examples. The scope of programs which can be generated by evolutionary approaches is, in principle, unrestricted, but generation times are typically high and there is no guarantee that such a program is found for which the fitness is optimal. We present a first study exploring possible benefits from combining analytical and evolutionary inductive programming. We use the analytical system Igor2 to generate skeleton programs which are used as initial hypotheses for the evolutionary system Adate. We can show that providing such constraints can reduce the induction time of Adate.} }
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Neil Crossley, Emanuel Kitzelmann, Martin Hofmann, and Ute Schmid.
Evolutionary Programming Guided by Analytically Generated Seeds.
In António Dourado, Agostinho C. Rosa, and Kurosh Madani,
editors, IJCCI'09: Proceedings of the International Joint Conference
on Computational Intelligence (Valencia, Spain, Oct.24-26, 2009), pages
198-203. INSTICC Press, 2009.
@inproceedings{crossley_ea:2009b, author = {Neil Crossley and Emanuel Kitzelmann and Martin Hofmann and Ute Schmid}, title = {{Evolutionary Programming Guided by Analytically Generated Seeds}}, editor = {Ant{\'o}nio Dourado and Agostinho C. Rosa and Kurosh Madani}, booktitle = {{IJCCI'09}: Proceedings of the International Joint Conference on Computational Intelligence (Valencia, Spain, Oct.\,24--26, 2009)}, year = 2009, pages = {198--203}, publisher = {INSTICC Press}, isbn = {978-989-674-014-6} }
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James Cussens and Alan M. Frisch, editors.
Inductive Logic Programming, 10th International Conference,
ILP'00, London, UK, July24-27, 2000. Proceedings, volume 1866 of
Lecture Notes in Computer Science, Berlin/Heidelberg, 2000. Springer.
@proceedings{cussens/frisch:2000, title = {Inductive Logic Programming, 10th International Conference, {ILP'00}, London, UK, July\,24--27, 2000. Proceedings}, year = 2000, editor = {James Cussens and Alan M. Frisch}, volume = 1866, series = {Lecture Notes in Computer Science}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-67795-6}, url = {http://www.springerlink.com/content/mtr4c2ntyngw/}, doi = {10.1007/3-540-44960-4} }
-
Allen Cypher.
Programming repetitive tasks by demonstration.
In Allen Cypher, editor, Watch What I Do: Programming by
Demonstration, pages 205-217. The MIT Press, 1993.
@incollection{cypher:1993, author = {Allen Cypher}, title = {Programming repetitive tasks by demonstration}, editor = {Allen Cypher}, booktitle = {Watch What I Do: Programming by Demonstration}, publisher = {The MIT Press}, year = 1993, pages = {205--217} }
-
Allen Cypher, editor.
Watch What I Do: Programming by Demonstration.
The MIT Press, 1993.
@book{cypher:1993b, editor = {Allen Cypher}, title = {Watch What I Do: Programming by Demonstration}, publisher = {The MIT Press}, year = 1993 }
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Luc De Raedt and Luc Dehaspe.
Clausal discovery.
Machine Learning, 26(2-3):99-146, February 1997.
@article{de-raedt/dehaspe:1997, author = {De~Raedt, Luc and Dehaspe, Luc}, title = {Clausal Discovery}, journal = {Machine Learning}, year = 1997, volume = 26, number = {2-3}, pages = {99--146}, month = {February}, publisher = {Springer Netherlands}, issn = {0885-6125 (Print) 1573-0565 (Online)}, url = {http://www.springerlink.com/content/j30702810h758166/}, doi = {10.1023/A:1007361123060}, keywords = {Inductive Logic Programming; Knowledge Discovery in Databases; Data Mining; Learning; Induction; Semantics for Induction; Logic of Induction; Parallel Learning}, abstract = {The clausal discovery engine claudien is presented. CLAUDIEN is an inductive logic programming engine that fits in the descriptive data mining paradigm. CLAUDIEN addresses characteristic induction from interpretations, a task which is related to existing formalisations of induction in logic. In characteristic induction from interpretations, the regularities are represented by clausal theories, and the data using Herbrand interpretations. Because CLAUDIEN uses clausal logic to represent hypotheses, the regularities induced typically involve multiple relations or predicates. CLAUDIEN also employs a novel declarative bias mechanism to define the set of clauses that may appear in a hypothesis.} }
-
Luc De Raedt, editor.
Advances in Inductive Logic Programming.
IOS Press, 1996.
@book{de-raedt:1996, editor = {De~Raedt, Luc}, title = {Advances in Inductive Logic Programming}, publisher = {IOS Press}, year = 1996, url = {http://books.google.de/books?id=GGN6jPacVy0C}, keywords = {book; ilp; induction; machine learning}, annote = {contains, amongst others, several contributions to the learning of recursive logic programs, thus interesting for inductive programming research} }
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Luc De Raedt.
Logical settings for concept-learning.
Artificial Intelligence, 95(1):187-201, 1997.
@article{de-raedt:1997, author = {De~Raedt, Luc}, title = {Logical Settings for Concept-Learning}, journal = {Artificial Intelligence}, year = 1997, volume = 95, number = 1, pages = {187--201}, address = {Essex, UK}, publisher = {Elsevier Science Publishers Ltd.}, url = {http://dx.doi.org/10.1016/S0004-3702(97)00041-6}, keywords = {ilp; learnability}, abstract = {Three different formalizations of concept-learning in logic (as well as some variants) are analyzed and related. It is shown that learning from interpretations reduces to learning from entailment, which in turn reduces to learning from satisfiability. The implications of this result for inductive logic programming and computational learning theory are then discussed, and guidelines for choosing a problem-setting are formulated.} }
-
Nachum Dershowitz.
Programming by analogy.
In Ryszard S. Michalski, Jaime G. Carbonell, and Tom M. Mitchell,
editors, Machine Learning. An Artificial Intelligence Approach,
volume 2, chapter 15, pages 393-422. Morgan Kaufmann, Los Altos, CA, 1986.
@incollection{dershowitz:1986, author = {Nachum Dershowitz}, title = {Programming by analogy}, editor = {Ryszard S. Michalski and Jaime G. Carbonell and Tom M. Mitchell}, booktitle = {Machine Learning. An Artificial Intelligence Approach}, publisher = {Morgan Kaufmann}, year = 1986, volume = 2, chapter = 15, pages = {393--422}, address = {Los Altos, CA} }
-
Yves Deville and Kung-Kiu Lau.
Logic program synthesis.
Journal of Logic Programming, 1994.
@article{deville/lau:1994, author = {Yves Deville and Kung-Kiu Lau}, title = {Logic Program Synthesis}, journal = {Journal of Logic Programming}, year = 1994, keywords = {deductive program synthesis; ilp; inductive programming; program synthesis; survey} }
-
Surnjani Djoko, Diane J. Cook, and Lawrence B. Holder.
An empirical study of domain knowledge and its benefits to
substructure discovery.
IEEE Transactions on Knowledge and Data Engineering,
9(4):575-586, 1997.
@article{djoko_ea:1997, author = {Surnjani Djoko and Diane J. Cook and Lawrence B. Holder}, title = {An Empirical Study of Domain Knowledge and Its Benefits to Substructure Discovery}, journal = {IEEE Transactions on Knowledge and Data Engineering}, year = 1997, volume = 9, number = 4, pages = {575--586}, address = {Piscataway, NJ, USA}, url = {http://dx.doi.org/10.1109/69.617051}, issn = {1041-4347}, publisher = {IEEE Educational Activities Department}, abstract = {Discovering repetitive, interesting, and functional substructures in a structural database improves the ability to interpret and compress the data. However, scientists working with a database in their area of expertise often search for predetermined types of structures or for structures exhibiting characteristics specific to the domain. The paper presents a method for guiding the discovery process with domain specific knowledge. The SUBDUE discovery system is used to evaluate the benefits of using domain knowledge to guide the discovery process. Domain knowledge is incorporated into SUBDUE following a single general methodology to guide the discovery process. Results show that domain specific knowledge improves the search for substructures that are useful to the domain and leads to greater compression of the data.} }
-
Martin Dostál.
On evolving of recursive functions using lambda abstraction and
higher-order functions.
Logic Journal of IGPL, 13(5):515-524, 2005.
@article{dostal:2005, author = {Martin Dost\'{a}l}, title = {On Evolving of Recursive Functions Using Lambda Abstraction and Higher-order Functions}, journal = {Logic Journal of IGPL}, year = 2005, volume = 13, number = 5, pages = { 515--524}, publisher = {Oxford University Press}, url = {http://jigpal.oxfordjournals.org/cgi/gca?sendit=Get+All+Checked+Abstract(s)&gca=13%2F5%2F515}, keywords = {enumerative ip; gp; higher-order functions; ifp; induction; inductive programming; program evolution; program synthesis} }
-
Martin Dostál.
A functional approach to evolving recursive programs.
In Emanuel Kitzelmann and Ute Schmid, editors, AAIP'07:
Proceedings of the 2nd Workshop on Approaches and Applications of Inductive
Programming (Warsaw, Poland, September17, 2007), pages 27-38, 2007.
Work in Progress Report.
@inproceedings{dostal:2007, author = {Martin Dost{\'a}l}, title = {A Functional Approach to Evolving Recursive Programs}, editor = {Emanuel Kitzelmann and Ute Schmid}, booktitle = {{AAIP'07}: Proceedings of the 2nd Workshop on Approaches and Applications of Inductive Programming (Warsaw, Poland, September\,17, 2007)}, year = 2007, pages = {27--38}, note = {Work in Progress Report}, url = {http://www.cogsys.wiai.uni-bamberg.de/aaip07/}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/aaip07/aaip_print.pdf}, keywords = {enumerative ip; gp; higher-order functions; induction; inductive programming; program evolution; program synthesis} }
-
Marko C. J. D. van Eekelen, editor.
TFP'05: Revised Selected Papers from the 6th Symposium on
Trends in Functional Programming (Tallinn, Estonia, Sep.23-24, 2005),
volume 6 of Trends in Functional Programming. Intellect, 2007.
@proceedings{eekelen:2007, title = {{TFP'05}: Revised Selected Papers from the 6th Symposium on Trends in Functional Programming (Tallinn, Estonia, Sep.\,23--24, 2005)}, year = 2007, editor = {Marko C. J. D. van Eekelen}, volume = 6, series = {Trends in Functional Programming}, publisher = {Intellect}, isbn = {978-1-84150-176-5} }
-
Hartmut Ehrig and Bernd Mahr.
Fundamentals of Algebraic Specification 1.
Springer, 1985.
@book{ehrig/mahr:1985, author = {Hartmut Ehrig and Bernd Mahr}, title = {Fundamentals of Algebraic Specification 1}, publisher = {Springer}, year = 1985, keywords = {algebraic specification} }
-
Esra Erdem and Pierre Flener.
A redefinition of least generalizations and its application to
inductive logic program synthesis.
Technical report, unknown, 1997.
@techreport{erdem/flener:1997, author = {Erdem, Esra and Flener, Pierre}, title = {{A redefinition of least generalizations and its application to inductive logic program synthesis}}, institution = {unknown}, year = 1997, documenturl = {http://www.cs.bilkent.edu.tr/tech-reports/1997/BU-CEIS-9718.ps.z} }
-
Esra Erdem and Pierre Flener.
Completing open logic programs by constructive induction.
International Journal of Intelligent Systems, 14(10):995-1019,
1999.
@article{erdem/flener:1999, author = {Esra Erdem and Pierre Flener}, title = {Completing open logic programs by constructive induction}, journal = {International Journal of Intelligent Systems}, year = 1999, volume = 14, number = 10, pages = {995--1019}, address = {Department of Computer Sciences, The University of Texas at Austin, Austin, Texas 78712, USA; Department of Information Science, Uppsala University, Box 311, S-751 05 Uppsala, Sweden}, publisher = {John Wiley & Sons}, url = {10.1002/(SICI)1098-111X(199910)14:10<995::AID-INT4>3.0.CO;2-W}, annote = {Wiley InterScience: Journal: Abstract} }
-
Floriana Esposito, Donato Malerba, and Francesca A. Lisi.
Induction of recursive theories in the normal ilp setting: Issues and
solutions.
In James Cussens and Alan M. Frisch, editors, Inductive Logic
Programming. 10th International Conference, ILP'00, London, UK,
July24-27, 2000, Proceedings, volume 1866 of Lecture Notes in
Computer Science, pages 93-111, Berlin/Heidelberg, 2000. Springer.
@inproceedings{esposito_ea:2000, author = {Floriana Esposito and Donato Malerba and Francesca A. Lisi}, title = {Induction of Recursive Theories in the Normal ILP Setting: Issues and Solutions}, editor = {James Cussens and Alan M. Frisch}, booktitle = {Inductive Logic Programming. 10th International Conference, {ILP'00}, London, UK, July\,24--27, 2000, Proceedings}, year = 2000, series = {Lecture Notes in Computer Science}, volume = 1866, pages = {93--111}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-67795-6}, url = {http://www.springerlink.com/content/vrmwvmc9dfv108re/}, doi = {10.1007/3-540-44960-4_6}, keywords = {ATRE; ilp; inductive programming; ip-system; program synthesis; recursion}, abstract = {Induction of recursive theories in the normal ILP setting is a complex task because of the non-monotonicity of the consistency property. In this paper we propose computational solutions to some relevant issues raised by the multiple predicate learningproblem. A separate-and-parallel-conquer search strategy is adopted to interleave the learning of clauses supplying predicateswith mutually recursive definitions. A novel generality order to be imposed to the search space of clauses is investigatedin order to cope with recursion in a more suitable way. The consistency recovery is performed by reformulating the currenttheory and by applying a layering technique based on the collapsed dependency graph. The proposed approach has been implementedin the ILP system ATRE and tested in the specific context of the document understanding problem within the WISDOM project.Experimental results are discussed and future directions are drawn.} }
-
V. Estruch, C. Ferri, J. Hernández-Orallo, and M. J. Ramírez-Quintana.
Generalisation operators for lists embedded in a metric space.
In Ute Schmid, Emanuel Kitzelmann, and Rinus Plasmeijer, editors,
Approaches and Applications of Inductive Programming. 3rd International
Workshop, AAIP'09, Edinburgh, UK, Sept.4, 2009. Revised Papers, volume
5812 of Lecture Notes in Computer Science, pages 117-139,
Berlin/Heidelberg, 2010. Springer.
@inproceedings{estruch_ea:2010, author = {V. Estruch and C. Ferri and J. Hern\'andez-Orallo and M. J. Ram\'{\i}rez-Quintana}, title = {Generalisation Operators for Lists Embedded in a Metric Space}, editor = {Ute Schmid and Emanuel Kitzelmann and Rinus Plasmeijer}, booktitle = {Approaches and Applications of Inductive Programming. 3rd International Workshop, {AAIP'09}, Edinburgh, UK, Sept.\,4, 2009. Revised Papers}, year = 2010, series = {Lecture Notes in Computer Science}, volume = 5812, pages = {117--139}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, documenturl = {http://www.springerlink.com/content/0151147952k37k54/fulltext.pdf}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-642-11930-9}, url = {http://www.springerlink.com/content/0151147952k37k54/}, abstract = {In some application areas, similarities and distances are used to calculate how similar two objects are in order to use these measurements to find related objects, to cluster a set of objects, to make classifications or to perform an approximate search guided by the distance. In many other application areas, we require patterns to describe similarities in the data. These patterns are usually constructed through generalisation (or specialisation) operators. For every data structure, we can define distances. In fact, we may find different distances for sets, lists, atoms, numbers, ontologies, web pages, etc. We can also define pattern languages and use generalisation operators over them. However, for many data structures, distances and generalisation operators are not consistent. For instance, for lists (or sequences), edit distances are not consistent with regular languages, since, for a regular pattern such as *}, keywords = {Distance-based methods; inductive operators; induction with distances; list-based representations}, doi = {10.1007/978-3-642-11931-6_6} }
-
C. Ferri-Ramírez, José Hernández-Orallo, and M. José
Ramírez-Quintana.
Incremental learning of functional logic programs.
In Functional and Logic Programming. 5th International
Symposium, FLOPS'01, Tokyo, Japan, March7-9, 2001. Proceedings, volume
2024 of Lecture Notes in Computer Science, pages 233-247,
Berlin/Heidelberg, 2001. Springer.
@inproceedings{ferri-ramirez_ea:2001, author = {C. Ferri-Ram{\'i}rez and Jos{\'e} Hern{\'a}ndez-Orallo and M. Jos{\'e} Ram{\'i}rez-Quintana}, title = {Incremental Learning of Functional Logic Programs}, booktitle = {Functional and Logic Programming. 5th International Symposium, {FLOPS'01}, Tokyo, Japan, March\,7--9, 2001. Proceedings}, year = 2001, series = {Lecture Notes in Computer Science}, volume = 2024, pages = {233--247}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-41739-2}, url = {http://www.springerlink.com/content/9kmf4guqdx8v8367/}, keywords = {flip; iflp; inductive programming; ip-system; program synthesis; recursion; Inductive functional logic programming (IFLP); inductive logic programming (ILP); incremental learning; theory revision}, doi = {10.1007/3-540-44716-4_15}, abstract = {In this work, we consider the extension of the Inductive Functional Logic Programming (IFLP) framework in order to learn functions in an incremental way. In general, incremental learning is necessary when the number of examples is infinite, very large orpresented one by one. We have performed this extension in the FLIP system, an implementation of the IFLP framework. Severalexamples of programs which have been induced indicate that our extension pays off in practice. An experimental study of someparameters which affect this efficiency is performed and some applications for programming practice are illustrated, especiallysmall classification problems and data-mining of semi-structured data.} }
-
Pierre Flener and Yves Deville.
Logic program transformation through generalization schemata.
In Logic Program Synthesis and Transformation. 5th International
Workshop, LOPSTR'95, Utrecht, The Netherlands, Sept.20-22, 1995.
Proceedings, volume 1048 of Lecture Notes in Computer Science, pages
171-173, Berlin/Heidelberg, 1996. Springer.
@inproceedings{flener/deville:1996, author = {Pierre Flener and Yves Deville}, title = {Logic Program Transformation through Generalization Schemata}, booktitle = {Logic Program Synthesis and Transformation. 5th International Workshop, {LOPSTR'95}, Utrecht, The Netherlands, Sept.\,20--22, 1995. Proceedings}, year = 1996, series = {Lecture Notes in Computer Science}, volume = 1048, pages = {171--173}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-60939-1}, url = {http://www.springerlink.com/content/f46v3640937r88g4/}, abstract = {Both generalization techniques are very suitable for mechanical transformation: all operators of the generalized programs are operators of the initial programs. Given a divide-and-conquer program, a mere inspection of the properties of its solving, processing, and composition operators thus allows the detection of which kinds of generalization are possible, and to which optimizations they would lead. Theeurekadiscoveries are compiled away, and the transformations can be completely automated.}, doi = {10.1007/3-540-60939-3_13}, keywords = {1995; Deville; Dialogs; Flener; inductive programming; inproceedings; logic programming}, annote = {Logic Program Transformation through Generalization Schemata - Flener, Deville (ResearchIndex)} }
-
Pierre Flener and Derek Partridge.
Inductive programming.
Automated Software Engineering, 8(2):131-137, April 2001.
@article{flener/partridge:2001, author = {Pierre Flener and Derek Partridge}, title = {Inductive Programming}, journal = {Automated Software Engineering}, year = 2001, volume = 8, number = 2, pages = {131--137}, month = {April}, url = {http://dx.doi.org/10.1023/A:1008797606116}, keywords = {article; ase; induction; inductive programming; position paper; program synthesis; software engineering} }
-
Pierre Flener and Lubos Popelinsky.
On the use of inductive reasoning in program synthesis: Prejudice and
prospects.
In L. Fribourg and F. Turini, editors, Logic Program Synthesis
and Transformation - Meta-Programming in Logic. 4th International
Workshops, LOPSTR'94 and META'94, Pisa, Italy, June20-21, 1994.
Proceedings, volume 883 of Lecture Notes in Computer Science, pages
69-87, Berlin/Heidelberg, 1994. Springer.
@inproceedings{flener/popelinsky:1994, author = {Pierre Flener and Lubos Popelinsky}, title = {On the Use of Inductive Reasoning in Program Synthesis: Prejudice and Prospects}, editor = {L. Fribourg and F. Turini}, booktitle = {Logic Program Synthesis and Transformation --- Meta-Programming in Logic. 4th International Workshops, {LOPSTR'94} and {META'94}, Pisa, Italy, June\,20--21, 1994. Proceedings}, year = 1994, series = {Lecture Notes in Computer Science}, volume = 883, pages = {69--87}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-58792-7}, url = {http://www.springerlink.com/content/y739v33lt5261p5p/}, doi = {10.1007/3-540-58792-6_5}, keywords = {ilp; inductive programming; inproceedings; position paper; program synthesis; software engineering}, abstract = {In this position paper, we give a critical analysis of the deductive and inductive approaches to program synthesis, and of the current research in these fields. From the shortcomings of these approaches and works, we identify future research directions for these fields, as well as a need for cooperation and cross-fertilization between them.} }
-
Pierre Flener and Ute Schmid.
An introduction to inductive programming.
Artificial Intelligence Review, 29(1):45-62, 2008.
@article{flener/schmid:2008, author = {Pierre Flener and Ute Schmid}, title = {An Introduction to Inductive Programming}, journal = {Artificial Intelligence Review}, year = 2008, volume = 29, number = 1, pages = {45--62}, keywords = {inductive programming} }
-
Pierre Flener and Serap Yilmaz.
Inductive synthesis of recursive logic programs: Achievements and
prospects.
The Journal of Logic Programming, 41(2-3):141-195,
November/December 1999.
@article{flener/yilmaz:1999, author = {Pierre Flener and Serap Yilmaz}, title = {Inductive Synthesis of Recursive Logic Programs: Achievements and Prospects}, journal = {The Journal of Logic Programming}, year = 1999, volume = 41, number = {2--3}, pages = {141--195}, month = {November\,/\,December}, annote = {Contains an overview of ilp systems for program synthesis.}, url = {http://dx.doi.org/10.1016/S0743-1066(99)00028-X}, keywords = {comparison; dialogs; ilp; inductive programming; ip-system; program synthesis; recursion; survey}, abstract = {The inductive synthesis of recursive logic programs from incomplete information, such as input/output examples, is a challenging subfield both of Inductive Logic Programming (ILP) and of the synthesis (in general) of logic programs, from formal specifications. We first overview past and present achievements, focusing on the techniques that were designed specifically for the inductive synthesis of recursive logic programs but also discussing a few general ILP techniques that can also induce non-recursive hypotheses. Then we analyse the prospects of these techniques in this task, investigating their applicability to software engineering as well as to knowledge acquisition and discovery.} }
-
Pierre Flener.
Logic Program Synthesis from Incomplete Information.
Kluwer Academic Publishers, Boston, 1995.
@book{flener:1995, author = {Pierre Flener}, title = {Logic Program Synthesis from Incomplete Information}, publisher = {Kluwer Academic Publishers}, year = 1995, address = {Boston}, keywords = {ilp; inductive programming; program synthesis} }
-
Pierre Flener.
Inductive logic program synthesis with DIALOGS.
In Stephen H. Muggleton, editor, ILP'96: Proceedings of the
6th International Workshop on Inductive Logic Programming (Stockholm, Sweden,
Aug.26-28, 1996), pages 28-51. Stockholm University, Royal Institute of
Technology, 1996.
@inproceedings{flener:1996, author = {Pierre Flener}, title = {Inductive logic program synthesis with {DIALOGS}}, editor = {Stephen H. Muggleton}, booktitle = {{ILP'96}: Proceedings of the 6th International Workshop on Inductive Logic Programming (Stockholm, Sweden, Aug.\,26--28, 1996)}, year = 1996, pages = {28--51}, publisher = {Stockholm University, Royal Institute of Technology}, keywords = {1996; Dialogs; Flener; inductive logic programming; inductive programming; inproceedings}, annote = {Inductive Logic Program Synthesis with DIALOGS - Flener (ResearchIndex)} }
-
Pierre Flener.
Inductive logic program synthesis with DIALOGS.
In Stephen H. Muggleton, editor, Inductive Logic Programming.
6th International Workshop, ILP'96, Stockholm, Sweden, Aug.26-28, 1996.
Selected Papers, volume 1314 of Lecture Notes in Computer Science,
pages 175-198, Berlin/Heidelberg, 1997. Springer.
@inproceedings{flener:1997, author = {Pierre Flener}, title = {Inductive Logic Program Synthesis with {DIALOGS}}, editor = {Stephen H. Muggleton}, booktitle = {Inductive Logic Programming. 6th International Workshop, {ILP'96}, Stockholm, Sweden, Aug.\,26--28, 1996. Selected Papers}, year = 1997, series = {Lecture Notes in Computer Science}, volume = 1314, pages = {175--198}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, keywords = {analytical ip; dialogs; ilp; inductive programming; ip-system; program synthesis; recursion}, abstract = {DIALOGS (Dialogue-based Inductive and Abductive LOGic program Synthesizer) is a schema-guided synthesizer of recursive logic programs; it takes the initiative and queries a (possibly computationally naive) specifier for evidence in her/his conceptual language. The specifier must know the answers to such simple queries, because otherwise s/he wouldn't even feel the need for the synthesized program. DIALOGS can be used by any learner (including itself) that detects, or merely conjectures, the necessity of invention of a new predicate. Due to its foundation on a powerful codification of a recursion-theory (by means of the template and constraints of a divide-and-conquer schema), DIALOGS needs very little evidence and is very fast.}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-63494-2}, url = {http://www.springerlink.com/content/67617138x2848145/}, doi = {10.1007/3-540-63494-0_55} }
-
Pierre Flener.
Achievements and prospects of program synthesis.
In A. C. Kakas and F. Sadri, editors, Computational Logic: Logic
Programming and Beyond. Essays in Honour of Robert A. Kowalski, Part I,
volume 2407 of Lecture Notes in Computer Science, pages 1-43,
Berlin/Heidelberg, 2002. Springer.
@inproceedings{flener:2002, author = {Pierre Flener}, title = {Achievements and prospects of program synthesis}, editor = {A. C. Kakas and F. Sadri}, booktitle = {Computational Logic: Logic Programming and Beyond. Essays in Honour of Robert A. Kowalski, Part I}, year = 2002, series = {Lecture Notes in Computer Science}, volume = 2407, pages = {1--43}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-43959-2}, url = {http://www.springerlink.com/content/uhur0dmfdp27t9ma/}, abstract = {Program synthesis research aims at developing a program that develops correct programs from specifications, with as much or as little interaction as the specifier wants. I overview the main achievements in deploying logic for program synthesis. I also outline the prospects of such research, arguing that, while the technology scales up from toy programs to real-life software and to commercially viable tools, computational logic will continue to be a driving force behind this progress.}, doi = {10.1007/3-540-45628-7_13} }
-
Pierre Flener, L. Popelinsky, and O. Stepankova.
Ilp and automatic programming: towards three approaches.
In ILP'94: Proceedings of the 4th International Workshop on
Inductive Logic Programming (Bonn, Germany, Sept.12-14, 1994), volume 237
of GMD-Studien, pages 351-364. Gesellschaft für Mathematik
und Datenverarbeitung MBH, 1994.
@inproceedings{flener_ea:1994, author = {Pierre Flener and L. Popelinsky and O. Stepankova}, title = {ILP and automatic programming: towards three approaches}, booktitle = {{ILP'94}: Proceedings of the 4th International Workshop on Inductive Logic Programming (Bonn, Germany, Sept.\,12--14, 1994)}, year = 1994, series = {{GMD}-Studien}, volume = 237, pages = {351--364}, publisher = {{G}esellschaft f{\"{u}}r {M}athematik und {D}atenverarbeitung {MBH}}, annote = {ute-inflit} }
-
Pierre Flener, Kung-Kiu Lau, and Mario Ornaghi.
On correct program schemas.
In Norbert E. Fuchs, editor, Logic Programming Synthesis and
Transformation. 7th International Workshop, LOPSTR'97, Leuven, Belgium,
July10-12, 1997. Proceedings, volume 1463 of Lecture Notes in
Computer Science, pages 128-147, Berlin/Heidelberg, 1998. Springer.
@inproceedings{flener_ea:1998, author = {Pierre Flener and Kung-Kiu Lau and Mario Ornaghi}, title = {On Correct Program Schemas}, editor = {Norbert E. Fuchs}, booktitle = {Logic Programming Synthesis and Transformation. 7th International Workshop, {LOPSTR'97}, Leuven, Belgium, July\,10--12, 1997. Proceedings}, year = 1998, series = {Lecture Notes in Computer Science}, volume = 1463, pages = {128--147}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-65074-4}, url = {http://www.springerlink.com/content/0j0rh135a1b2r7l1/}, abstract = {We present our work on the representation and correctness of program schemas, in the context of logic program synthesis. Whereas most researchers represent schemas purely syntactically as higher-order expressions, we shall express a schema as an open first-order theory that axiomatises a problem domain, called aspecification framework, containing an open program that represents the template of the schema. We will show that using our approach we can define a meaningful notion of correctness for schemas, viz. that correct program schemas can be expressed asparametricspecification frameworks containing templates that aresteadfast, i.e. programs that are always correct provided their open relations are computed correctly.}, subject_collection = {Computer Science}, doi = {10.1007/3-540-49674-2_7} }
-
Maarten M. Fokkinga.
Monadic Maps and Folds for Arbitrary Datatypes.
Technical Report Memoranda Inf 94-28, University of Twente,
Enschede, Netherlands, June 1994.
@techreport{fokkinga:1994, author = {Fokkinga, Maarten M.}, title = {{Monadic Maps and Folds for Arbitrary Datatypes}}, institution = {University of Twente}, year = 1994, number = {Memoranda Inf 94--28}, address = {Enschede, Netherlands}, month = {June}, abstract = {Each datatype constructor comes equiped not only with a so-called map and fold (catamorphism), as is widely known, but, under some condition, also with a kind of map and fold that are related to an arbitrary given monad. This result follows from the preservation of initiality under lifting from the category of algebras in a given category to a certain other category of algebras in the Kleisli category related to the monad. }, pages = {1--23} }
-
R. Freivalds.
Inductive inference of recursive functions: qualitative theory.
In J. M. Barzdinš and D. Bjorner, editors,
Baltic Computer Science. Selected Papers, volume 502 of Lecture Notes
in Computer Science, pages 77-110. Springer, Berlin/Heidelberg, 1991.
@incollection{freivalds:1991, author = {R. Freivalds}, title = {Inductive inference of recursive functions: qualitative theory}, editor = {B{\=a}rzdi{\c{n}}{\v{s}}, J. M. and Bjorner, D.}, booktitle = {Baltic Computer Science. Selected Papers}, publisher = {Springer}, year = 1991, volume = 502, series = {Lecture Notes in Computer Science}, pages = {77--110}, address = {Berlin\,/\,Heidelberg}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-54131-8}, url = {http://www.springerlink.com/content/57332j2671j7p508/}, doi = {10.1007/BFb0019359}, annote = {ute-inflit} }
-
Mitsue Furusawa, Nobuhiro Inuzuka, Hirohisa Seki, and Hidenori Itoh.
Induction of logic programs with more than one recursive clause by
analyzing saturations.
In Nada Lavrač and Sašo Džeroski, editors,
Inductive Logic Programming. 7th International Workshop, ILP'97, Prague,
Czech Republic, Sept.17-20, 1997, Proceedings, volume 1297 of
Lecture Notes in Computer Science, pages 165-172, Berlin/Heidelberg,
1997. Springer.
@inproceedings{furusawa_ea:1997, author = {Mitsue Furusawa and Nobuhiro Inuzuka and Hirohisa Seki and Hidenori Itoh}, title = {Induction of Logic Programs with More than One Recursive Clause by Analyzing Saturations}, editor = {Nada Lavra{\v{c}} and Sa{\v{s}}o D{\v{z}}eroski}, booktitle = {Inductive Logic Programming. 7th International Workshop, {ILP'97}, Prague, Czech Republic, Sept.\,17--20, 1997, Proceedings}, year = 1997, series = {Lecture Notes in Computer Science}, volume = 1297, pages = {165--172}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, isbn = {978-3-540-63514-7}, issn = {0302-9743 (Print) 1611-3349 (Online)}, url = {http://www.springerlink.com/content/c75726877p674419/}, doi = {10.1007/3540635149_45}, keywords = {MRI; ilp; inductive programming; ip-system; program synthesis; recursion}, abstract = {This paper describes a bottom-up ILP algorithm called MRI, which induces recursive programs with one or more recursive clauses from a few of examples. It analyzes saturations using path structures, which express streams of terms processed by predicates and was originally introduced by Identam-Almquist. We introduce extension and difference of path structures. Recursive clauses can be expressed as a difference among path structures. The paper also shows experimental results.} }
-
Malik Ghallab, Dana Nau, and Paolo Traverso.
Automated Planning: theory and practice.
Morgan Kaufmann, 2004.
@book{ghallab_ea:2004, author = {Malik Ghallab and Dana Nau and Paolo Traverso}, title = {Automated Planning: theory and practice}, publisher = {Morgan Kaufmann}, year = 2004, keywords = {planning} }
-
J. Y. Girard.
Une extension de l'interprétation de gödel àl'analyse, et
son application à l'élimination des coupures dans l'analyse et la
théorie des types.
In Jens Erik Fenstad, editor, Proceedings of the 2nd
Scandinavian Logic Symposium (University of Oslo, June18-20, 1970),
volume 63 of Studies in logic and the foundations of mathematics, pages
63-92. North-Holland, 1971.
@inproceedings{girard:1971, author = {J. Y. Girard}, title = {Une extension de l'interpr\'{e}tation de G\"{o}del \`{a}l'analyse, et son application \`{a} l'\'{e}limination des coupures dans l'analyse et la th\'{e}orie des types}, editor = {Jens Erik Fenstad}, booktitle = {Proceedings of the 2nd Scandinavian Logic Symposium (University of Oslo, June\,18--20, 1970)}, year = 1971, series = {Studies in logic and the foundations of mathematics}, volume = 63, pages = {63--92}, publisher = {North-Holland}, isbn = 0720422590, keywords = {lambda calculus; recursion theory; seminal paper; system f}, annote = {one of the two original system f works} }
-
Joseph A. Goguen.
How to prove algebraic inductive hypotheses without induction.
In 5th Conference on Automated Deduction. Les Arcs, France,
July8-11, 1980, volume 87 of Lecture Notes in Computer Science,
pages 356-373, Berlin/Heidelberg, 1980. Springer.
@inproceedings{goguen:1980, author = {Joseph A. Goguen}, title = {How to Prove Algebraic Inductive Hypotheses without Induction}, booktitle = {5th Conference on Automated Deduction. Les Arcs, France, July\,8--11, 1980}, year = 1980, series = {Lecture Notes in Computer Science}, volume = 87, pages = {356--373}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-10009-6}, url = {http://www.springerlink.com/content/f61317u230575416/}, doi = {10.1007/3-540-10009-1_27}, keywords = {algebraic specification; equational logic; term rewriting}, abstract = {This paper proves the correctness of algebraic methods for deciding the equivalence of expressions by applying rewrite rules, and for proving inductive equational hypotheses without using induction; it also shows that the equations true in the initial algebra are just those provable by structural induction. The major results generalize, simplify and rigorize Musser's method for proving inductive hypotheses with the Knuth-Bendix algorithm; our approach uses a very general result, that (under certain conditions) an equation is true iff it is consistent. Finally, we show how these results can be extended to proving the correctness of an implementation of one data abstraction by another.} }
-
E. Mark Gold.
Language identification in the limit.
Information and Control, 10(5):447-474, 1967.
@article{gold:1967, author = {E. Mark Gold}, title = {Language Identification in the Limit}, journal = {Information and Control}, year = 1967, volume = 10, number = 5, pages = {447--474}, url = {http://www.isrl.uiuc.edu/~amag/langev/paper/gold67limit.html}, keywords = {article; identification in the limit; induction; machine learning; seminal paper}, annote = {golds seminal paper on inductive inference}, abstract = {Language learnability has been investigated. This refers to the following situation: A class of possible languages is specified, together with a method of presenting information to the learner about an unknown language, which is to be chosen from the class. The question is now asked, ``Is the information sufficient to determine which of the possible languages is the unknown language?'' Many definitions of learnability are possible, but only the following is considered here: Time is quantized and has a finite starting time. At each time the learner receives a unit of information and is to make a guess as to the identity of the unknown language on the basis of the information received so far. This process continues forever. The class of languages will be considered learnable with respect to the specified method of information presentation if there is an algorithm that the learner can use to make his guesses, the algorithm having the following property: Given any language of the class, there is some finite time after which the guesses will all be the same and they will be correct. In this preliminary investigation, a language is taken to be a set of strings on some finite alphabet. The alphabet, is the same for all languages of the class. Several variations of each of the following two basic methods of information presentation are investigated: A text for a language generates the strings of the language in any order such that every string of the language occurs at. least once. An informant for a language tells whether a string is in the language, and chooses the strings in some order such that every string occurs at least once. It was found that the class of context-sensitive languages is learnable from an informant, but that, not even the class of regular languages is learnable from a text. } }
-
E. Marc Gold.
Complexity of automaton identification from given data.
Information and Control, 37:302-320, 1978.
@article{gold:1978, author = {E. Marc Gold}, title = {Complexity of automaton identification from given data}, journal = {Information and Control}, year = 1978, volume = 37, pages = {302--320} }
-
Palem GopalaKrishna.
Data-dependencies and learning in artificial systems.
In Emanuel Kitzelmann, Roland J. Olsson, and Ute Schmid, editors,
AAIP'05: Proceedings of the 1st Workshop on Approaches and
Applications of Inductive Programming (Bonn, Germany, Aug.7, 2005), pages
69-78, 2005.
Work in Progress Reports.
@inproceedings{gopalakrishna:2005, author = {Palem GopalaKrishna}, title = {Data-dependencies and Learning in Artificial Systems }, editor = {Emanuel Kitzelmann and Roland J. Olsson and Ute Schmid}, booktitle = {{AAIP'05}: Proceedings of the 1st Workshop on Approaches and Applications of Inductive Programming (Bonn, Germany, Aug.\,7, 2005)}, year = 2005, pages = {69--78}, note = {Work in Progress Reports}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/aaip05/proceedings/DataDependenciesInLearning.pdf} }
-
C. C. Green and D. R. Barstow.
On program synthesis knowledge.
Artificial Intelligence, 10:241-279, 1978.
@article{green/barstow:1978, author = {C. C. Green and D. R. Barstow}, title = {On program synthesis knowledge}, journal = {Artificial Intelligence}, year = 1978, volume = 10, pages = {241--279} }
-
Masami Hagiya and T. Sakurai.
Foundation of logic programming based on inductive definition.
New Generation Computing, 2(1):59-77, 1984.
@article{hagiya/sakurai:1984, author = {Hagiya, Masami and Sakurai, T.}, title = {Foundation of logic programming based on inductive definition}, journal = {New Generation Computing}, year = 1984, volume = 2, number = 1, pages = {59--77}, publisher = {Springer} }
-
Masami Hagiya.
Programming by example and proving by example using higher-order
unification.
In 10th International Conference on Automated Deduction.
Kaiserslautern, FRG, July24-27, 1990. Proceedings, volume 449 of
Lecture Notes in Computer Science, pages 588-602, Berlin/Heidelberg,
1990. Springer.
@inproceedings{hagiya:1990, author = {Hagiya, Masami}, title = {Programming by example and proving by example using higher-order unification}, booktitle = {10th International Conference on Automated Deduction. Kaiserslautern, {FRG}, July\,24--27, 1990. Proceedings}, year = 1990, series = {Lecture Notes in Computer Science}, volume = 449, pages = {588--602}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-52885-2}, url = {http://www.springerlink.com/content/p4543uux655h1647/}, doi = {10.1007/3-540-52885-7_116}, keywords = {ifp; induction; inductive programming; inproceedings; program synthesis}, abstract = {We propose a new approach to programming by example, in which a program is synthesized from examples by higher-order unification in a type theory with a recursion operator. The approach, when applied to the problem of proof generalization, makes it possible to synthesize a general proof from a concrete example proof and establish a method of proving by example. Cases in which a program and a proof are simultaneously synthesized are also considered. In order to represent proofs as terms and generalize proof terms by higher-order unification, we extend Logical Framework to a system with product and equality.} }
-
Lutz Hamel and Chi Shen.
Inductive acquisition of algebraic specifications.
In WADT'06: Proceedings of the Workshop for Algebraic
Development Techniques (La Roche en Ardenne, Belgium, June1-3, 2006),
2006.
@inproceedings{hamel/shen:2006, author = {Lutz Hamel and Chi Shen}, title = {Inductive Acquisition of Algebraic Specifications}, booktitle = {{WADT'06}: Proceedings of the Workshop for Algebraic Development Techniques (La Roche en Ardenne, Belgium, June\,1--3, 2006)}, year = 2006, documenturl = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.107.8027&rep=rep1&type=pdf} }
-
Lutz Hamel and Chi Shen.
An inductive programming approach to algebraic specification.
In Emanuel Kitzelmann and Ute Schmid, editors, AAIP'07:
Proceedings of the 2nd Workshop on Approaches and Applications of Inductive
Programming (Warsaw, Poland, September17, 2007), pages 3-14, 2007.
Invited Talk.
@inproceedings{hamel/shen:2007, author = {Lutz Hamel and Chi Shen}, title = {An Inductive Programming Approach to Algebraic Specification}, editor = {Emanuel Kitzelmann and Ute Schmid}, booktitle = {{AAIP'07}: Proceedings of the 2nd Workshop on Approaches and Applications of Inductive Programming (Warsaw, Poland, September\,17, 2007)}, year = 2007, pages = {3--14}, note = {Invited Talk}, keywords = {algebraic specification; enumerative ip; ifp; induction; inductive programming; program evolution; program synthesis}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/aaip07/aaip_print.pdf}, url = {http://www.cogsys.wiai.uni-bamberg.de/aaip07/} }
-
Lutz Hamel.
Breeding algebraic structures - an evolutionary approach to
inductive equational logic programming.
In GECCO'02: Proceedings of the 4th Annual Conference on
Genetic and Evolutionary Computation (New York, USA, July09-13, 2002),
pages 748-755, San Francisco, CA, USA, 2002. Morgan Kaufmann.
@inproceedings{hamel:2002, author = {Lutz Hamel}, title = {Breeding Algebraic Structures -- An Evolutionary Approach To Inductive Equational Logic Programming}, booktitle = {{GECCO'02}: Proceedings of the 4th Annual Conference on Genetic and Evolutionary Computation (New York, USA, July\,09--13, 2002)}, year = 2002, pages = {748--755}, address = {San Francisco, CA, USA}, publisher = {Morgan Kaufmann}, isbn = {1-55860-878-8}, url = {http://portal.acm.org/citation.cfm?id=646205.683098}, keywords = {algebraic specification; enumerative ip; ifp; induction; inductive programming; program evolution; program synthesis}, annote = {Breeding Algebraic Structures - An Evolutionary Approach To Inductive Equational Logic Programming} }
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Andreas Hamfelt, Jørgen Fischer Nilsson, and Nikolaj Oldager.
Logic program synthesis as problem reduction using combining forms.
Automated Software Engineering, 8(2):167-193, 2001.
@article{hamfelt_ea:2001, author = {Andreas Hamfelt and J\o rgen Fischer Nilsson and Nikolaj Oldager}, title = {Logic Program Synthesis as Problem Reduction Using Combining Forms}, journal = {Automated Software Engineering}, year = 2001, volume = 8, number = 2, pages = {167--193}, publisher = {Springer Netherlands}, issn = {0928-8910 (Print) 1573-7535 (Online)}, url = {http://www.springerlink.com/content/g66225t50x26844k/}, abstract = {This paper presents an approach to inductive synthesis of logic programs from examples using problem decomposition and problem reduction principles. This is in contrast to the prevailing logic program induction paradigm, which relies on generalization of programs from examples. The problem reduction is accomplished as a constrained top-down search process, which eventually is to reach trivial problems.Our induction scheme applies a distinguished logic programming language in which programs are combined from elementary predicates by means of combinators conceived of as problem reduction operators including list recursion forms. The operator form admits inductive synthesis as a top-down piecewise composition of semantically meaningful program elements according to the compositional semantics principle and with appeals neither to special generalization mechanisms nor to alternative forms of resolution and unification, or predicate invention.The search space is reduced by subjecting the induction process to various constraints concerning syntactical form, modes, data types, and computational resources. This is illustrated in the paper with well-modedness constraints with the aim of synthesising well-moded, procedurally acceptable programs.Preliminary experiments with the proposed induction method lead us to tentatively conclude that the presented approach forms a viable alternative to the prevailing inductive logic programming methods applying generalization from examples.}, doi = {10.1023/A:1008741507024}, keywords = {article; ase; combilog; combinduce; enumerative ip; ilp; induction; inductive programming; program synthesis; recursion schemes} }
-
Michael Hanus, editor.
Logic-Based Program Synthesis and Transformation, 18th
International Symposium, LOPSTR'08, Valencia, Spain, July 17-18, 2008,
Revised Selected Papers, volume 5438 of Lecture Notes in Computer
Science, Berlin/Heidelberg, 2009. Springer.
@proceedings{hanus:2009, title = {Logic-Based Program Synthesis and Transformation, 18th International Symposium, {LOPSTR'08}, Valencia, Spain, July 17--18, 2008, Revised Selected Papers}, year = 2009, editor = {Michael Hanus}, volume = 5438, series = {Lecture Notes in Computer Science}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-642-00514-5}, url = {http://www.springerlink.com/content/u06956481x17/}, doi = {10.1007/978-3-642-00515-2} }
-
S. Hardy.
Synthesis of LISP functions from examples.
In IJCAI'75: Proceedings of the 4th International Joint
Conference on Artificial Intelligence (Tbilisi, Georgia, USSR, Sept.3-8,
1975), pages 240-245, 1975.
@inproceedings{hardy:1975, author = {S. Hardy}, title = {Synthesis of {LISP} Functions from Examples}, booktitle = {{IJCAI}'75: Proceedings of the 4th International Joint Conference on Artificial Intelligence (Tbilisi, Georgia, USSR, Sept.\,3--8, 1975)}, year = 1975, pages = {240--245}, documenturl = {http://dli.iiit.ac.in/ijcai/IJCAI-75-VOL-1&2/PDF/034.pdf}, keywords = {ifp; induction; inductive programming; lisp; pre-summers; program synthesis} }
-
K. Hausmann.
Iterative and recursive modes of thinking in mathematical problem
solving processes.
In L. Streefland, editor, PME'95: Proceedings of the 9th
International Conference for the Psychology of Mathematical Education
(Noordwijkerhout, The Netherlands, 1985), pages 18-23. State University,
1985.
@inproceedings{hausmann:1985, author = {K. Hausmann}, title = {Iterative and recursive modes of thinking in mathematical problem solving processes}, editor = {L. Streefland}, booktitle = {{PME'95}: Proceedings of the 9th International Conference for the Psychology of Mathematical Education (Noordwijkerhout, The Netherlands, 1985)}, year = 1985, pages = {18--23}, publisher = {State University} }
-
K. Haussmann and M. Reiss.
Logo beginners problems with goal merging.
In J. Hillel, editor, LME3: Proceedings of the 3rd
International Conference for LOGO and Mathematics Education, pages 156-163.
Concordia University, Montreal, Canada, 1987.
@incollection{haussmann/reiss:1987, author = {K. Haussmann and M. Reiss}, title = {LOGO beginners problems with goal merging}, editor = {J. Hillel}, booktitle = {{LME3}: Proceedings of the 3rd International Conference for LOGO and Mathematics Education}, publisher = {Concordia University}, year = 1987, pages = {156--163}, address = {Montreal, Canada} }
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Robert Henderson.
Incremental learning in inductive programming.
In Ute Schmid, Emanuel Kitzelmann, and Rinus Plasmeijer, editors,
Approaches and Applications of Inductive Programming. 3rd International
Workshop, AAIP'09, Edinburgh, UK, Sept.4, 2009. Revised Papers, volume
5812 of Lecture Notes in Computer Science, pages 74-92,
Berlin/Heidelberg, 2010. Springer.
@inproceedings{henderson:2010, author = {Robert Henderson}, title = {Incremental Learning in Inductive Programming}, editor = {Ute Schmid and Emanuel Kitzelmann and Rinus Plasmeijer}, booktitle = {Approaches and Applications of Inductive Programming. 3rd International Workshop, {AAIP'09}, Edinburgh, UK, Sept.\,4, 2009. Revised Papers}, year = 2010, series = {Lecture Notes in Computer Science}, volume = 5812, pages = {74--92}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-642-11930-9}, url = {http://www.springerlink.com/content/1h137673x2428841/}, abstract = {Inductive programming systems characteristically exhibit an exponential explosion in search time as one increases the size of the programs to be generated. As a way of overcoming this, we introduce}, keywords = {Inductive programming; inductive functional programming; incremental learning}, doi = {10.1007/978-3-642-11931-6_4}, documenturl = {http://www.springerlink.com/content/1h137673x2428841/fulltext.pdf} }
-
José Hernández-Orallo and M. JoséRamírez-Quintana.
Inverse narrowing for the induction of functional logic programs.
In José Luis Freire-Nistal, Moreno Falaschi, and Manuel Vilares
Ferro, editors, APPIA-GULP-PRODE'98: Joint Conference on Declarative
Programming (A Coruña, Spain, July20-23, 1998), pages 379-392, 1998.
@inproceedings{hernandez-orallo/joseramirez-quintana:1998, author = {Jos{\'e} Hern{\'a}ndez-Orallo and M. Jos{\'e}Ram{\'i}rez-Quintana}, title = {Inverse Narrowing for the Induction of Functional Logic Programs}, editor = {Jos{\'e} Luis Freire-Nistal and Moreno Falaschi and Manuel Vilares Ferro}, booktitle = {{APPIA-GULP-PRODE'98}: Joint Conference on Declarative Programming (A Coru{\~n}a, Spain, July\,20--23, 1998)}, year = 1998, pages = {379--392}, keywords = {flip; iflp; inductive programming; ip-system; program synthesis; recursion} }
-
José Hernández-Orallo and M. JoséRamírez-Quintana.
A Strong Complete Schema for Inductive Functional Logic
Programming.
In Saso Dzeroski and Peter A. Flach, editors, Inductive Logic
Programming. 9th International Workshop, ILP'99, Bled, Slovenia,
June24-27, 1999. Proceedings, volume 1634 of Lecture Notes in
Computer Science. Lecture Notes in Artificial Intelligence, pages 116-127,
Berlin/Heidelberg, 1999. Springer.
@inproceedings{hernandez-orallo/joseramirez-quintana:1999, author = {Jos{\'e} Hern{\'a}ndez-Orallo and M. Jos{\'e}Ram{\'i}rez-Quintana}, title = {{A} {S}trong {C}omplete {S}chema for {I}nductive {F}unctional {L}ogic {P}rogramming.}, editor = {Saso Dzeroski and Peter A. Flach}, booktitle = {Inductive Logic Programming. 9th International Workshop, {ILP'99}, Bled, Slovenia, June\,24--27, 1999. Proceedings}, year = 1999, series = {Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence}, volume = 1634, pages = {116--127}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, keywords = {flip; ifp; inductive programming; ip-system; program synthesis; recursion}, annote = {A Strong Complete Schmema for Inductive Functional Logic Programming}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-66109-2}, url = {http://www.springerlink.com/content/qxg8na20hwvug2nd/}, abstract = {A new IFLP schema is presented as a general framework for the induction of functional logic programs (FLP). Since narrowing (which is the most usual operational semantics of (FLP) performs a infication (mgu) followed by a replacement, we introduce two main operators in our IFLP schema: a generalisation and an inverse replacement or property of equality. We prove that this schema isstrongcomplete in tha way that, given some evidence, it is possible to induce any program which could have generated that evidence. We outline some possible restrictions in order to improve the tractability of the schema. We also show that inverse narrowing is just a special case of our IFLP schema. Finally, a straightforward extension of the IFLP schema to function invention is illustrated.}, doi = {10.1007/3-540-48751-4_12} }
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Thomas Hieber and Martin Hofmann.
Automated Method Induction: Functional Goes Object Oriented.
In Ute Schmid, Emanuel Kitzelmann, and Rinus Plasmeijer, editors,
Approaches and Applications of Inductive Programming. 3rd International
Workshop, AAIP'09, Edinburgh, UK, Sept.4, 2009. Revised Papers, volume
5812 of Lecture Notes in Computer Science, pages 159-173,
Berlin/Heidelberg, 2010. Springer.
@inproceedings{hieber/hofmann:2010, author = {Thomas Hieber and Martin Hofmann}, title = {{Automated Method Induction: Functional Goes Object Oriented}}, editor = {Ute Schmid and Emanuel Kitzelmann and Rinus Plasmeijer}, booktitle = {Approaches and Applications of Inductive Programming. 3rd International Workshop, {AAIP'09}, Edinburgh, UK, Sept.\,4, 2009. Revised Papers}, year = 2010, series = {Lecture Notes in Computer Science}, volume = 5812, pages = {159--173}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-642-11930-9}, url = {http://www.springerlink.com/content/64563727294h5052/}, abstract = {The development of software engineering has had a great deal of benefits for the development of software. Along with it came a whole new paradigm of the way software is designed and implemented - object orientation. Today it is a standard to have UML diagrams translated into program code wherever possible. However, as few tools really go beyond this we demonstrate a simple functional representation for objects, methods and object-properties. In addition we show how our inductive programming system}, doi = {10.1007/978-3-642-11931-6_8}, documenturl = {http://www.springerlink.com/content/64563727294h5052/fulltext.pdf} }
-
Thomas Hieber, Martin Hofmann, Emanuel Kitzelmann, and Ute Schmid.
Programming recursive functions by examples.
In B. Velichkovsky Leon Urbas, T. Goschke, editor,
Tagungsbericht der 9. Jahrestagung der Gesellschaft für
Kognitionswissenschaft (KogWis 2008, TU Dresden, 28.9.-1.10. 2008), 2008.
Nominiert für den Brain Products Poster Preis im Rahmender
KogWis'08 (Platz 2).
@inproceedings{hieber_ea:2008, author = {Thomas Hieber and Martin Hofmann and Emanuel Kitzelmann and Ute Schmid}, title = {Programming Recursive Functions By Examples}, editor = {Leon Urbas, T. Goschke, B. Velichkovsky}, booktitle = {Tagungsbericht der 9. Jahrestagung der Gesellschaft f{\"u}r Kognitionswissenschaft ({KogWis} 2008, TU Dresden, 28.9.--1.10. 2008)}, year = 2008, note = {Nominiert f{\"u}r den Brain Products Poster Preis im Rahmender {KogWis'08} (Platz 2)}, isbn = {978-3-939025-14-6} }
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Martin Hofmann and Emanuel Kitzelmann.
Input/Output guided detection of list catamorphisms: Towards
problem specific use of program templates in IP.
In John Gallagher and Janis Voigtländer, editors,
Proceedings of the ACM SIGPLAN Workshop on Partial Evaluation and Program
Manipulation (PEPM'10, Madrid, Jan.18-19, 2010), pages 93-100, New
York, NY, USA, 2010. ACM Press.
Co-located with POPL'10 (37th ACM SIGACT-SIGPLAN Symposium on
Principles of Programming Languages (Madrid, Spain, Jan.18-22, 2010).
@inproceedings{hofmann/kitzelmann:2010, author = {Hofmann, Martin and Kitzelmann, Emanuel}, title = {{Input/Output} Guided Detection of List Catamorphisms: Towards Problem Specific Use of Program Templates in {IP}}, editor = {John Gallagher and Janis Voigtl\"{a}nder}, booktitle = {Proceedings of the {ACM} {SIGPLAN} Workshop on Partial Evaluation and Program Manipulation ({PEPM'10}, Madrid, Jan.\,18--19, 2010)}, year = 2010, pages = {93--100}, address = {New York, NY, USA}, publisher = {{ACM} Press}, note = {Co-located with {POPL'10} (37th {ACM} {SIGACT-SIGPLAN} Symposium on Principles of Programming Languages (Madrid, Spain, Jan.\,18--22, 2010)}, isbn = {978-1-60558-727-1}, keywords = {higher-order functions; inductive programming} }
-
Martin Hofmann.
Automatic Construction of XSL Templates - An Inductive
Programming Approach.
VDM Verlag, Saarbrücken, 2007.
@book{hofmann:2007, author = {Martin Hofmann}, title = {{Automatic Construction of {XSL} Templates --- An Inductive Programming Approach}}, publisher = {VDM Verlag}, year = 2007, address = {Saarbr\"{u}cken}, school = {University of Bamberg}, isbn = {978-3-639-00194-5}, pages = 124, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/theses/hofmann/hofmann.pdf} }
-
Martin Hofmann.
Igor2 - an analytical inductive functional programming system: Tool
demo.
In John Gallagher and Janis Voigtländer, editors,
Proceedings of the ACM SIGPLAN Workshop on Partial Evaluation and Program
Manipulation (PEPM'10, Madrid, Jan.18-19, 2010), pages 29-32, New
York, NY, USA, 2010. ACM Press.
Co-located with POPL'10 (37th ACM SIGACT-SIGPLAN Symposium on
Principles of Programming Languages (Madrid, Spain, Jan.18-22, 2010).
@inproceedings{hofmann:2010, author = {Hofmann, Martin}, title = {Igor2 -- An Analytical Inductive Functional Programming System: Tool Demo}, editor = {John Gallagher and Janis Voigtl{\"a}nder}, booktitle = {Proceedings of the {ACM} {SIGPLAN} Workshop on Partial Evaluation and Program Manipulation ({PEPM'10}, Madrid, Jan.\,18--19, 2010)}, year = 2010, pages = {29--32}, address = {New York, NY, USA}, publisher = {{ACM} Press}, note = {Co-located with {POPL'10} (37th {ACM} {SIGACT-SIGPLAN} Symposium on Principles of Programming Languages (Madrid, Spain, Jan.\,18--22, 2010)}, isbn = {978-1-60558-727-1}, url = {http://doi.acm.org/10.1145/1706356.1706364} }
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Martin Hofmann.
Data-driven detection of catamorphisms - towards prolem specific
use of program schemes for inductive program synthesis.
In TFP'10: Proceedings of the 11th Symposium on Trends in
Functional Programming, (University of Oklahoma, Oklahoma City, USA,
May17-19, 2010, 2010.
@inproceedings{hofmann:2010b, author = {Hofmann, Martin}, title = {Data-Driven Detection of Catamorphisms --- Towards Prolem Specific Use of Program Schemes for Inductive Program Synthesis}, booktitle = {{TFP'10}: Proceedings of the 11th Symposium on Trends in Functional Programming, (University of Oklahoma, Oklahoma City, USA, May\,17--19, 2010}, year = 2010 }
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Martin Hofmann, Andreas Hirschberger, Emanuel Kitzelmannn, and Ute Schmid.
Inductive Synthesis of Recursive Functional Programs - A Comparison
of Three Systems.
In J. Hertzberg, M. Beetz, and R. Englert, editors, KI'07:
Advances in Artificial Intelligence. 30th Annual German Conference on AI,
KI'07, Osnabrück, Germany, Sept.10-13, 2007. Proceedings, volume 4667
of Lecture Notes in Computer Science, pages 468-472,
Berlin/Heidelberg, 2007. Springer.
@inproceedings{hofmann_ea:2007, author = {Martin Hofmann and Andreas Hirschberger and Emanuel Kitzelmannn and Ute Schmid}, title = {{Inductive Synthesis of Recursive Functional Programs -- A Comparison of Three Systems}}, editor = {Hertzberg, J. and Beetz, M. and Englert, R.}, booktitle = {KI'07: Advances in Artificial Intelligence. 30th Annual German Conference on AI, {KI'07}, Osnabr\"uck, Germany, Sept.\,10--13, 2007. Proceedings }, year = 2007, series = {Lecture Notes in Computer Science}, volume = 4667, pages = {468--472}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, abstract = {One of the most challenging subfields, and a still little researched niche of machine learning, is the inductive synthesis of recursive programs from incomplete specifications, such as examples for the desired input/output behavior.}, keywords = {2007; adate; atre; automatic programming; dialogs; functional programming; ilp; induction; inductive; inductive functional programming; inductive inference; inductive learning; inductive logic programming; inductive program synthesis; inductive programming; inproceedings; programming; published; }, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-74564-8}, url = {http://www.springerlink.com/content/p03v78658627t0l2/}, doi = {10.1007/978-3-540-74565-5_42} }
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Martin Hofmann, Emanuel Kitzelmann, and Ute Schmid.
Analysis and evaluation of inductive programming systems in a
higher-order framework.
In A. Dengel, K. Berns, T. M. Breuel, F. Bomarius, and T. R.
Roth-Berghofer, editors, KI'08: Advances in Artificial Intelligence.
31st Annual German Conference on AI, KI'08, Kaiserslautern, Germany,
Sept.23-26, 2008. Proceedings, volume 5243 of Lecture Notes in
Computer Science. Lecture Notes in Artificial Intelligence, pages 78-86,
Berlin/Heidelberg, 2008. Springer.
@inproceedings{hofmann_ea:2008, author = {Martin Hofmann and Emanuel Kitzelmann and Ute Schmid}, title = {Analysis and Evaluation of Inductive Programming Systems in a Higher-Order Framework}, editor = {A. Dengel and K. Berns and T. M. Breuel and F. Bomarius and T. R. Roth-Berghofer}, booktitle = {{KI'08}: Advances in Artificial Intelligence. 31st Annual German Conference on AI, {KI'08}, Kaiserslautern, Germany, Sept.\,23--26, 2008. Proceedings}, year = 2008, series = {Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence}, volume = 5243, pages = {78--86}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-85844-7}, url = {http://www.springerlink.com/content/8348l7120633677l/}, abstract = {In this paper we present a comparison of several inductive programming (IP) systems. IP addresses the problem of learning (recursive) programs from incomplete specifications, such as input/output examples. First, we introduce conditional higher-order term rewriting as a common framework for inductive program synthesis. Then we characterise the ILP systemGolemand the inductive functional systemMagicHaskellerwithin this framework. In consequence, we propose the inductive functional systemIgorII as a powerful and efficient approach to IP. Performance of all systems on a representative set of sample problems is evaluated and shows the strength ofIgorII.}, doi = {10.1007/978-3-540-85845-4_10}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/publications/KI2008_submission_49(4).pdf}, keywords = {analytical ip; enumerative ip; experiment; haskell; higher-order functions; iflp; ifp; igor2; ilp; induction; inductive programming; inproceedings; machine learning; overview; program synthesis} }
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Martin Hofmann, Emanuel Kitzelmann, and Ute Schmid.
A unifying framework for analysis and evaluation of inductive
programming systems.
In B. Goertzel, P. Hitzler, and M. Hutter, editors, Artificial
General Intelligence. AGI'09: Proceedings of the 2nd Conference on
Artificial General Intelligence (Arlington, Virginia, March6-9 2009),
Advances in Intelligent Systems Research, pages 55-60. Atlantis Press, 2009.
@inproceedings{hofmann_ea:2009, author = {Martin Hofmann and Emanuel Kitzelmann and Ute Schmid}, title = {A Unifying Framework for Analysis and Evaluation of Inductive Programming Systems}, editor = {B. Goertzel and P. Hitzler and M. Hutter}, booktitle = {Artificial General Intelligence. {AGI'09}: Proceedings of the 2nd Conference on Artificial General Intelligence (Arlington, Virginia, March\,6--9 2009)}, year = 2009, series = {Advances in Intelligent Systems Research}, pages = {55--60}, publisher = {Atlantis Press}, isbn = {978-90-78677-24-6}, url = {http://dx.doi.org/10.2991/agi.2009.16}, keywords = {inductive programming}, abstract = {In this paper we present a comparison of several inductive programming (IP) systems. IP addresses the problem of learning (recursive) programs from incomplete specifications, such as input/output examples. First, we introduce conditional higher-order term rewriting as a common framework for inductive logic and inductive functional program synthesis. Then we characterise the several ILP systems which belong either to the most recently researched or currently to the most powerful IP systems within this framework. In consequence, we propose the inductive functional system Igor2 as a powerful and efficient approach to IP. Performance of all systems on a representative set of sample problems is evaluated and shows the strength of Igor2.} }
-
Martin Hofmann, Emanuel Kitzelmann, and Ute Schmid.
Porting Igor2 from Maude to Haskell.
In Ute Schmid, Emanuel Kitzelmann, and Rinus Plasmeijer, editors,
Approaches and Applications of Inductive Programming. 3rd International
Workshop, AAIP'09, Edinburgh, UK, Sept.4, 2009. Revised Papers, volume
5812 of Lecture Notes in Computer Science, pages 140-158,
Berlin/Heidelberg, 2010. Springer.
@inproceedings{hofmann_ea:2010, author = {Martin Hofmann and Emanuel Kitzelmann and Ute Schmid}, title = {{Porting {Igor2} from {Maude} to {Haskell}}}, editor = {Ute Schmid and Emanuel Kitzelmann and Rinus Plasmeijer}, booktitle = {Approaches and Applications of Inductive Programming. 3rd International Workshop, {AAIP'09}, Edinburgh, UK, Sept.\,4, 2009. Revised Papers}, year = 2010, series = {Lecture Notes in Computer Science}, volume = 5812, pages = {140--158}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-642-11930-9}, url = {http://www.springerlink.com/content/w70304785057224g/}, abstract = {This paper describes our efforts and solutions in porting our IP system}, doi = {10.1007/978-3-642-11931-6_7}, documenturl = {http://www.springerlink.com/content/w70304785057224g/fulltext.pdf} }
-
Chad Hogg and Hector Munoz-Avila.
Learning hierarchical task networks from plan traces.
In Proceedings of the Workshop on Artificial Intelligence
Planning and Learning (Providence, Rhode Island, USA, Sept.22, 2007),
2007.
In conjunction with the International Conference on Automated
Planning and Scheduling (ICAPS'07).
@inproceedings{hogg/munoz-avila:2007, author = {Chad Hogg and Hector Munoz-Avila}, title = {Learning Hierarchical Task Networks from Plan Traces}, booktitle = {Proceedings of the Workshop on Artificial Intelligence Planning and Learning (Providence, Rhode Island, USA, Sept.\,22, 2007)}, year = 2007, note = {In conjunction with the International Conference on Automated Planning and Scheduling ({ICAPS'07})}, url = {http://www.cs.umd.edu/~ukuter/icaps07aipl/}, keywords = {learning-and-planning read} }
-
Marcus Hutter, Eric Baum, and Emanuel Kitzelmann, editors.
Artificial General Intelligence. AGI'10: Proceedings of the
3rd Conference on Artificial General Intelligence (Lugano, Switzerland,
March5-8, 2010), Advances in Intelligent Systems Research. Atlantis
Press, 2010.
@proceedings{hutter_ea:2010, title = {Artificial General Intelligence. {AGI'10}: Proceedings of the 3rd Conference on Artificial General Intelligence (Lugano, Switzerland, March\,5--8, 2010)}, year = 2010, editor = {Marcus Hutter and Eric Baum and Emanuel Kitzelmann}, series = {Advances in Intelligent Systems Research}, publisher = {Atlantis Press}, isbn = {978-90-78677-36-9}, keywords = {AGI; AI} }
-
Graham Hutton.
A tutorial on the universality and expressiveness of fold.
Journal of Functional Programming, 9:355-372, 1993.
@article{hutton:1993, author = {Graham Hutton}, title = {A Tutorial on the Universality and Expressiveness of Fold}, journal = {{Journal of Functional Programming}}, year = 1993, volume = 9, pages = {355--372}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.34.1618} }
-
Peter Idestam-Almquist.
Generalization under implication by recursive anti-unification.
In P. Utgoff, editor, ICML'93: Proceedings of the 10th
International Conference on Machine Learning (University of Massachusetts,
Amherst, MA, USA, June27-29, 1993), pages 151-158. Morgan Kaufmann,
1993.
@inproceedings{idestam-almquist:1993, author = {Idestam-Almquist, Peter}, title = {Generalization under Implication by Recursive Anti-unification}, editor = {P. Utgoff}, booktitle = {{ICML'93}: Proceedings of the 10th International Conference on Machine Learning (University of Massachusetts, Amherst, MA, USA, June\,27--29, 1993)}, year = 1993, pages = {151--158}, publisher = {Morgan Kaufmann}, isbn = {1-55860-307-7}, annote = {ute-inflit} }
-
Peter Idestam-Almquist.
Recursive anti-unification.
In Stephen H. Muggleton, editor, ILP'93: Proceedings Third
International Workshop on Inductive Logic Programming (Ljubljana, Slovenia,
1993), pages 241-254. JSI, 1993.
@inproceedings{idestam-almquist:1993b, author = {Idestam-Almquist, Peter}, title = {Recursive anti-unification}, editor = {Stephen H. Muggleton}, booktitle = {{ILP'93}: Proceedings Third International Workshop on Inductive Logic Programming (Ljubljana, Slovenia, 1993)}, year = 1993, pages = {241--254}, publisher = {JSI} }
-
Peter Idestam-Almquist.
Efficient induction of recursive definitions by structural analysis
of saturations.
In Luc De Raedt, editor, ILP'95: Proceedings of the 5th
International Workshop on Inductive Logic Programming (Tokyo, Japan,
June17, 1995, 1995.
@inproceedings{idestam-almquist:1995, author = {Idestam-Almquist, Peter}, title = {Efficient Induction of Recursive Definitions by Structural Analysis of Saturations}, editor = {De~Raedt, Luc}, booktitle = {{ILP'95}: Proceedings of the 5th International Workshop on Inductive Logic Programming (Tokyo, Japan, June\,17, 1995}, year = 1995 }
-
Peter Idestam-Almquist.
Efficient induction of recursive definitions by structural analysis
of saturations.
In Luc De Raedt, editor, Advances in Inductive Logic
Programming. IOS Press, 1996.
@incollection{idestam-almquist:1996, author = {Idestam-Almquist, Peter}, title = {Efficient Induction of Recursive Definitions by Structural Analysis of Saturations}, editor = {De~Raedt, Luc}, booktitle = {Advances in Inductive Logic Programming}, publisher = {IOS Press}, year = 1996, keywords = {analytical ip; ilp; inductive programming; ip-system; program synthesis; recursion; tim} }
-
Nobuhiro Inuzuka, Masakage Kamo, Naohiro Ishii, Hirohisa Seki, and Hidenori
Itoh.
Top-down induction of logic programs from incomplete samples.
In Inductive Logic Programming. 6th International Workshop,
ILP-96 Stockholm, Sweden, Aug.26-28, 1996. Selected Papers, volume 1314
of Lecture Notes in Computer Science, pages 265-282,
Berlin/Heidelberg, 1997. Springer.
@inproceedings{inuzuka_ea:1997, author = {Nobuhiro Inuzuka and Masakage Kamo and Naohiro Ishii and Hirohisa Seki and Hidenori Itoh}, title = {Top-down Induction of Logic Programs from Incomplete Samples}, booktitle = {Inductive Logic Programming. 6th International Workshop, {ILP-96} Stockholm, Sweden, Aug.\,26--28, 1996. Selected Papers}, year = 1997, series = {Lecture Notes in Computer Science}, volume = 1314, pages = {265--282}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, keywords = {FOIL-I; ilp; inductive programming; ip-system; program synthesis; recursion}, abstract = {We propose an ILP system FOIL-I, which induces logic programs by a top-down method from incomplete samples. An incomplete sample is constituted by some of positive examples and negative examples on a finite domain. FOIL-I has an evaluation function to estimate candidate definitions, the function which is composition of an information-based function and an encoding complexity measure. FOILI uses a best-first search using the evaluation function to make use of suspicious but necessary candidates. Other particular points include a treatment for recursive definitions and removal of redundant clauses. Randomly selected incomplete samples are tested with FOIL-I, QuinIan's FOIL and Muggleton's Progol. Compared with others FOIL-I can induce target relations in many cases from small incomplete samples.}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-63494-2}, url = {http://www.springerlink.com/content/7811x2g2695417x5/}, doi = {10.1007/3-540-63494-0_60} }
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A. Ishino and A. Yamamoto.
Learning from examples with typed equational programming.
In Algorithmic Learning Theory. 4th International Workshop on
Analogical and Inductive Inference (AII'94, 5th International Workshop on
Algorithmic Learning Theory (ALT'94), Reinhardsbrunn Castle, Germany
Oct.10-15, 1994. Proceedings, volume 872 of Lecture Notes in
Computer Science, pages 301-316. Springer, Berlin/Heidelberg, 1994.
@incollection{ishino/yamamoto:1994, author = {A. Ishino and A. Yamamoto}, title = {Learning from examples with typed equational programming}, booktitle = {Algorithmic Learning Theory. 4th International Workshop on Analogical and Inductive Inference ({AII'94}, 5th International Workshop on Algorithmic Learning Theory ({ALT'94}), Reinhardsbrunn Castle, Germany Oct.\,10--15, 1994. Proceedings}, publisher = {Springer}, year = 1994, volume = 872, series = {Lecture Notes in Computer Science}, pages = {301--316}, address = {Berlin\,/\,Heidelberg}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-58520-6}, url = {http://www.springerlink.com/content/f01326533257lh32/}, abstract = {In this paper we present a constructive method of learning from examples using typed equational programming. The main contribution is a concept of type maintenance which appears to be theoretically and practically useful. Type maintenance is based on polymorphic types and is not applicable to a type system without polymorphism. Because equational programming possesses good properties of both functional programming and logic programming, we will refine results in inductive inference of logic programs and that of functions. Our learning method is based on the type maintenance, the generalization given by Plotkin and Arimura et al. and the technique finding recursion given by Summers.}, doi = {10.1007/3-540-58520-6_73} }
-
Alon Itai and Michael Slavkin.
Detecting data structures from traces.
In Emanuel Kitzelmann and Ute Schmid, editors, AAIP'07:
Proceedings of the 2nd Workshop on Approaches and Applications of Inductive
Programming (Warsaw, Poland, September17, 2007), pages 39-50, 2007.
Work in Progress Report.
@inproceedings{itai/slavkin:2007, author = {Alon Itai and Michael Slavkin}, title = {Detecting Data Structures from Traces}, editor = {Emanuel Kitzelmann and Ute Schmid}, booktitle = {{AAIP'07}: Proceedings of the 2nd Workshop on Approaches and Applications of Inductive Programming (Warsaw, Poland, September\,17, 2007)}, year = 2007, pages = {39--50}, note = {Work in Progress Report}, url = {http://www.cogsys.wiai.uni-bamberg.de/aaip07/}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/aaip07/aaip_print.pdf} }
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J.-J. Jeng and B. H. C. Cheng.
Using analogy and formal methods for software reuse.
In ICTAI'93: Proceedings of the Fifth International Conference
on Tools with Artificial Intelligence (Boston, Massachusetts, USA,
Nov.l8-11, 1993), pages 113-117, Los Alamitos, CA, USA, November 1993.
IEEE Computer Society Press.
@inproceedings{jeng/cheng:1993, author = {J.-J. Jeng and B. H. C. Cheng}, title = {Using Analogy and Formal Methods for Software Reuse}, booktitle = {{ICTAI'93}: Proceedings of the Fifth International Conference on Tools with Artificial Intelligence (Boston, Massachusetts, USA, Nov.\,l8--11, 1993)}, year = 1993, pages = {113--117}, address = {Los Alamitos, CA, USA}, month = {November}, publisher = {IEEE Computer Society Press}, isbn = {0-8186-4200-9} }
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Johan Jeuring, Alexey Rodriguez, and Gideon Smeding.
Generating generic functions.
In Ralf Hinze, editor, WGP'06: Proceedings of the ACM
SIGPLAN Workshop on Generic Programming (Portland, Oregon, USA, Sept.16,
2006), pages 23-32, New York, NY, USA, 2006. ACM.
Featured by ICFP'06: 11th ACM SIGPLAN International Conference
on Functional Programming (Portland, Oregon, Sept.18-20, 2006).
@inproceedings{jeuring_ea:2006, author = {Johan Jeuring and Alexey Rodriguez and Gideon Smeding}, title = {Generating generic functions}, editor = {Ralf Hinze}, booktitle = {{WGP'06}: Proceedings of the {ACM} {SIGPLAN} Workshop on Generic Programming (Portland, Oregon, USA, Sept.\,16, 2006)}, year = 2006, pages = {23--32}, address = {New York, NY, USA}, publisher = {{ACM}}, note = {Featured by {ICFP'06}: 11th {ACM} {SIGPLAN} International Conference on Functional Programming (Portland, Oregon, Sept.\,18--20, 2006)}, url = {http://doi.acm.org/10.1145/1159861.1159865}, isbn = {1-59593-492-6}, keywords = {automated testing; enumerative ip; generic programming; higher-order functions; ifp; induction; inductive programming; inproceedings; program synthesis}, abstract = {We present an approach to the generation of generic functions from user-provided specifications. The specifications consist of the type of a generic function, examples of instances that it should "match" when specialized, and properties that the generic function should satisfy. We use the type-based function generator Djinn to generate terms for specializations of the generic function types on the type indices of generic functions. Then we use QuickCheck to prune the generated terms by testing against properties, and by testing specialized candidate functions against the provided examples. Using this approach we have been able to generate generic equality, map, and zip functions, for example.} }
-
Alípio Jorge and Pavel Brazdil.
Architecture for iterative learning of recursive definitions.
In Luc De Raedt, editor, Advances in Inductive Logic
Programming. IOS Press, 1996.
@incollection{jorge/brazdil:1996, author = {Al\'{i}pio Jorge and Pavel Brazdil}, title = {Architecture for Iterative Learning of Recursive Definitions}, editor = {De~Raedt, Luc}, booktitle = {Advances in Inductive Logic Programming}, publisher = {IOS Press}, year = 1996, keywords = {SKILit; ilp; inductive programming; ip-system; program synthesis; recursion}, annote = {main technique: iterative bootstrap induction} }
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Alípio M. G. Jorge.
Iterative Induction of Logic Programs.
PhD thesis, Departamento de Ciência de Computadores, Universidade
do Porto, 1998.
@phdthesis{jorge:1998, author = {Al\'{i}pio M. G. Jorge}, title = {Iterative Induction of Logic Programs}, school = {Departamento de Ci\^{e}ncia de Computadores, Universidade do Porto}, year = 1998, url = {http://www.liaad.up.pt/~amjorge/PhDThesis/}, keywords = {SKILit; ilp; inductive programming; ip-system; program synthesis; recursion} }
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J. P. Jouannaud and Yves Kodratoff.
Characterization of a class of functions synthesized from examples by
a Summers like method using a `B.M.W.'matching technique.
In IJCAI'79: Proceedings of the 6th International Joint
Conference on Artificial Intelligence (Tokyo, Japan, Aug.20-23, 1979),
pages 440-447. Morgan Kaufmann, 1979.
@inproceedings{jouannaud/kodratoff:1979, author = {J. P. Jouannaud and Yves Kodratoff}, title = {Characterization of a Class of Functions Synthesized from Examples by a {Summers} like method using a {`B.M.W.'}Matching Technique}, booktitle = {{IJCAI}'79: Proceedings of the 6th International Joint Conference on Artificial Intelligence (Tokyo, Japan, Aug.\,20--23, 1979)}, year = 1979, pages = {440--447}, publisher = {Morgan Kaufmann}, keywords = {analytical ip; ifp; induction; inductive programming; program synthesis; synthesis from traces} }
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Jean-Pierre Jouannaud and Yves Kodratoff.
Program synthesis from examples of behavior.
In Alan W. Biermann and Gérard Guiho, editors, Computer
Program Synthesis Methodologies, pages 213-250. D. Reidel Publ. Co., 1983.
@incollection{jouannaud/kodratoff:1983, author = {Jean-Pierre Jouannaud and Yves Kodratoff}, title = {Program Synthesis from Examples of Behavior}, editor = {Alan W. Biermann and G\'{e}rard Guiho}, booktitle = {Computer Program Synthesis Methodologies}, publisher = {D. Reidel Publ. Co.}, year = 1983, pages = {213--250}, keywords = {analytical ip; ifp; induction; inductive programming; program synthesis} }
-
Stefan Kahrs.
Genetic programming with primitive recursion.
In GECCO'06: Proceedings of the 8th Proceedings of the 8th
annual Conference on Genetic and Evolutionary Computation (Seattle,
Washington, USA, July08-12, 2006), pages 941-942, New York, NY, USA,
2006. ACM.
Poster Session “Genetic programming: posters”.
@inproceedings{kahrs:2006, author = {Stefan Kahrs}, title = {Genetic Programming with Primitive Recursion}, booktitle = {{GECCO'06}: Proceedings of the 8th Proceedings of the 8th annual Conference on Genetic and Evolutionary Computation (Seattle, Washington, USA, July\,08--12, 2006)}, year = 2006, pages = {941--942}, address = {New York, NY, USA}, publisher = {{ACM}}, note = {Poster Session ``Genetic programming: posters''}, url = {http://doi.acm.org/10.1145/1143997.1144160}, keywords = {enumerative ip; gp; ifp; induction; inductive programming; primitive recursion; program evolution; program synthesis}, abstract = {When Genetic Programming is used to evolve arithmetic functions it often operates by composing them from a fixed collection of elementary operators and applying them to parameters or certain primitive constants. This limits the expressiveness of the programs that can be evolved. It is possible to extend the expressiveness of such an approach significantly without leaving the comfort of terminating programs by including primitive recursion as a control operation.The technique used here was gene expression programming [2], a variation of grammatical evolution [8]. Grammatical evolution avoids the problem of program bloat; its separation of genotype (string of symbols) and phenotype (expression tree) permits to optimise the generated programs without interfering with the evolutionary process.} }
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Stefan Kahrs.
The primitive recursive functions are recursively enumerable, 2008.
@misc{kahrs:2008, author = {Stefan Kahrs}, title = {The Primitive Recursive Functions are Recursively Enumerable}, year = 2008, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.62.9712}, documenturl = {http://www.cs.kent.ac.uk/people/staff/smk/primrec.pdf}, keywords = {computability; recursion theory}, abstract = {Abstract. Meta-operations on primitive recursive functions sit at the brink of what is computationally possible: the semantic equality of primitive recursive programs is undecidable, and yet this paper shows that the whole class of p.r. functions can be enumerated without semantic duplicates. More generally, the construction shows that for any equivalence relation \approx on natural numbers, N/ \approx is r.e. if \approx is co-semi-decidable.} }
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Susumu Katayama.
Power of brute-force search in strongly-typed inductive functional
programming automation.
In Chengqi Zhang, Hans W. Guesgen, and Wai-Kiang Yeap, editors,
PRICAI'04: Trends in Artificial Intelligence. 8th Pacific Rim International
Conference on Artificial Intelligence, Auckland, New Zealand, Aug.9-13,
2004. Proceedings, volume 3157 of Lecture Notes in Computer Science,
pages 75-84, Berlin/Heidelberg, 2004. Springer.
@inproceedings{katayama:2004, author = {Susumu Katayama}, title = {Power of Brute-Force Search in Strongly-Typed Inductive Functional Programming Automation}, editor = {Chengqi Zhang and Hans W. Guesgen and Wai-Kiang Yeap}, booktitle = {{PRICAI'04}: Trends in Artificial Intelligence. 8th Pacific Rim International Conference on Artificial Intelligence, Auckland, New Zealand, Aug.\,9--13, 2004. Proceedings}, year = 2004, series = {Lecture Notes in Computer Science}, volume = 3157, pages = {75--84}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-22817-2}, url = {http://springerlink.metapress.com/content/u6gc1dt4yl9cmpkl/}, doi = {10.1007/978-3-540-28633-2_10}, abstract = {A successful case of applying brute-force search to functional programming automation is presented and compared with a conventional genetic programming method. From the information of the type and the property that should be satisfied, this algorithm is able to find automatically the shortest Haskell program using the set of function components (or library) configured beforehand, and there is no need to design the library every time one requests a new functional program. According to the presented experiments, programs consisted of several function applications can be found within some seconds even if we always use the library designed for general use. In addition, the proposed algorithm can efficiently tell the number of possible functions of given size that are consistent with the given type, and thus can be a tool to evaluate other methods like genetic programming by providing the information of the baseline performance.}, keywords = {MagicHaskeller; PolyGP; comparison; enumerative ip; higher-order functions; ifp; induction; inductive programming; program synthesis; } }
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Susumu Katayama.
Library for systematic search for expressions.
In AIC'06: Proceedings of the 6th WSEAS International
Conference on Applied Informatics and Communications (Elounda, Agios
Nikolaos, Crete Island, Greece, Aug.18-20, 2006), pages 381-387, Stevens
Point, Wisconsin, USA, 2006. World Scientific and Engineering Academy and
Society (WSEAS).
@inproceedings{katayama:2006, author = {Katayama, Susumu}, title = {Library for systematic search for expressions}, booktitle = {{AIC'06}: Proceedings of the 6th {WSEAS} International Conference on Applied Informatics and Communications (Elounda, Agios Nikolaos, Crete Island, Greece, Aug.\,18--20, 2006)}, year = 2006, pages = {381--387}, address = {Stevens Point, Wisconsin, USA}, publisher = {World Scientific and Engineering Academy and Society (WSEAS)}, isbn = {960-8457-51-3} }
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Susumu Katayama.
Systematic search for lambda expressions.
In Marko C. J. D. van Eekelen, editor, TFP'05: Revised
Selected Papers from the Sixth Symposium on Trends in Functional Programming
(Tallinn, Estonia, Sep.23-24, 2005), volume 6 of Trends in
Functional Programming, pages 111-126. Intellect Books, 2007.
@inproceedings{katayama:2007, author = {Susumu Katayama}, title = {Systematic Search for Lambda Expressions}, editor = {Marko C. J. D. van Eekelen}, booktitle = {{TFP'05}: Revised Selected Papers from the Sixth Symposium on Trends in Functional Programming (Tallinn, Estonia, Sep.\,23--24, 2005)}, year = 2007, series = {Trends in Functional Programming}, volume = 6, pages = {111--126}, publisher = {Intellect Books}, isbn = {978-1-84150-176-5}, documenturl = {http://www.cs.ioc.ee/tfp-icfp-gpce05/tfp-proc/14num.pdf}, keywords = {MagicHaskeller; enumerative ip; higher-order functions; ifp; induction; inductive programming; inproceedings; program synthesis; recursion schemes} }
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Susumu Katayama.
Efficient exhaustive generation of functional programs using
monte-carlo search with iterative deepening.
In PRICAI'08: Trends in Artificial Intelligence. 10th Pacific
Rim International Conference on Artificial Intelligence, Hanoi, Vietnam,
Dec.15-19, 2008. Proceedings, volume 5351 of Lecture Notes in
Computer Science, pages 199-210, Berlin/Heidelberg, 2008. Springer.
@inproceedings{katayama:2008, author = {Susumu Katayama}, title = {Efficient Exhaustive Generation of Functional Programs Using Monte-Carlo Search with Iterative Deepening}, booktitle = {{PRICAI'08}: Trends in Artificial Intelligence. 10th Pacific Rim International Conference on Artificial Intelligence, Hanoi, Vietnam, Dec.\,15--19, 2008. Proceedings}, year = 2008, series = {Lecture Notes in Computer Science}, volume = 5351, pages = {199--210}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-89196-3}, url = {http://www.springerlink.com/content/mh400717k763u162/}, abstract = {Genetic programming and inductive synthesis of functional programs are two major approaches to inductive functional programming. Recently, in addition to them, some researchers pursue efficient exhaustive program generation algorithms, partly for the purpose of providing a comparator and knowing how essential the ideas such as heuristics adopted by those major approaches are, partly expecting that approaches that exhaustively generate programs with the given type and pick up those which satisfy the given specification may do the task well. In exhaustive program generation, since the number of programs exponentially increases as the program size increases, the key to success is how to restrain the exponential bloat by suppressing semantically equivalent but syntactically different programs. In this paper we propose an algorithm applying random testing of program equivalences (or Monte-Carlo search for functional differences) to the search results of iterative deepening, by which we can totally remove redundancies caused by semantically equivalent programs. Our experimental results show that applying our algorithm to subexpressions during program generation remarkably reduces the computational costs when applied to rich primitive sets.}, doi = {10.1007/978-3-540-89197-0_21} }
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Susumu Katayama.
Recent improvements of magichaskeller.
In Ute Schmid, Emanuel Kitzelmann, and Rinus Plasmeijer, editors,
Approaches and Applications of Inductive Programming. 3rd International
Workshop, AAIP'09, Edinburgh, UK, Sept.4, 2009. Revised Papers, volume
5812 of Lecture Notes in Computer Science, pages 174-193,
Berlin/Heidelberg, 2010. Springer.
@inproceedings{katayama:2010, author = {Susumu Katayama}, title = {Recent Improvements of MagicHaskeller}, editor = {Ute Schmid and Emanuel Kitzelmann and Rinus Plasmeijer}, booktitle = {Approaches and Applications of Inductive Programming. 3rd International Workshop, {AAIP'09}, Edinburgh, UK, Sept.\,4, 2009. Revised Papers}, year = 2010, series = {Lecture Notes in Computer Science}, volume = 5812, pages = {174--193}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-642-11930-9}, url = {http://www.springerlink.com/content/ejx67u1835q7j757/}, abstract = {MagicHaskeller is our inductive functional programming library based on systematic search. In this paper we introduce two recent improvements to MagicHaskeller, i.e. 1) clarification and extension to arbitrary-rank polymorphism of its algorithm, and 2) efficiency improvement in its filtration algorithm that removes redundancy in the search results.}, doi = {10.1007/978-3-642-11931-6_9}, keywords = {inductive programming; magichaskeller}, documenturl = {http://www.springerlink.com/content/ejx67u1835q7j757/fulltext.pdf} }
-
Oleg Kiselyov and Ralf Lämmel.
Haskell's overlooked object system, 2005.
@misc{kiselyov/laemmel:2005, author = {Oleg Kiselyov and Ralf L\"ammel}, title = {Haskell's overlooked object system}, year = 2005, url = {http://www.citebase.org/abstract?id=oai:arXiv.org:cs/0509027} }
-
Oleg Kiselyov, Ralf Lämmel, and Keean Schupke.
Strongly typed heterogeneous collections.
In Haskell'04: Proceedings of the ACM SIGPLAN workshop on
Haskell (Snowbird, Utah, USA, Sept.22-22, 2004), pages 96-107. ACM
Press, 2004.
@inproceedings{kiselyov_ea:2004, author = {Oleg Kiselyov and Ralf L{\"a}mmel and Keean Schupke}, title = {{Strongly typed heterogeneous collections}}, booktitle = {{Haskell'04}: Proceedings of the {ACM} {SIGPLAN} workshop on Haskell (Snowbird, Utah, USA, Sept.\,22--22, 2004)}, year = 2004, pages = {96--107}, publisher = {{ACM} Press}, url = {http://doi.acm.org/10.1145/1017472.1017488}, isbn = {1-58113-850-4} }
-
Emanuel Kitzelmann and Martin Hofmann.
IgorII: An inductive functional programming prototype.
In Mailik Ghallab, Constantine D. Spyropoulos, Nikos Fakotakis, and
Nikos Avouris, editors, ECAI'08: Proceedings of the System
Demonstrations of the 18th European Conference on Artificial Intelligence
(Patras, Greece, July21-25, 2008), volume 178 of Frontiers in
Artificial Intelligence and Applications, pages 29-30, Amsterdam,
Netherlands, 2008. IOS Press.
@inproceedings{kitzelmann/hofmann:2008, author = {Emanuel Kitzelmann and Martin Hofmann}, title = {{IgorII}: An Inductive Functional Programming Prototype}, editor = {Mailik Ghallab and Constantine D. Spyropoulos and Nikos Fakotakis and Nikos Avouris}, booktitle = {{ECAI'08}: Proceedings of the System Demonstrations of the 18th European Conference on Artificial Intelligence (Patras, Greece, July\,21--25, 2008)}, year = 2008, series = {Frontiers in Artificial Intelligence and Applications}, volume = 178, pages = {29--30}, address = {Amsterdam, Netherlands}, publisher = {IOS Press}, isbn = {978-960-6843-17-4} }
-
Emanuel Kitzelmann and Ute Schmid.
An explanation based generalization approach to inductive synthesis
of functional programs.
In Emanuel Kitzelmann, Roland J. Olsson, and Ute Schmid, editors,
AAIP'05: Proceedings of the 1st Workshop on Approaches and
Applications of Inductive Programming (Bonn, Germany, Aug.7, 2005), pages
15-26, 2005.
Full Paper.
@inproceedings{kitzelmann/schmid:2005, author = {Emanuel Kitzelmann and Ute Schmid}, title = {An Explanation Based Generalization Approach to Inductive Synthesis of Functional Programs}, editor = {Emanuel Kitzelmann and Roland J. Olsson and Ute Schmid}, booktitle = {{AAIP'05}: Proceedings of the 1st Workshop on Approaches and Applications of Inductive Programming (Bonn, Germany, Aug.\,7, 2005)}, year = 2005, pages = {15--26}, note = {Full Paper}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/aaip05/proceedings/aaip05_ifps.pdf}, keywords = {analytical ip; ebg; ifp; igor1; induction; inductive programming; inproceedings; machine learning; program synthesis; recursive program schemes} }
-
Emanuel Kitzelmann and Ute Schmid.
Inductive synthesis of functional programs: An explanation based
generalization approach.
Journal of Machine Learning Research, 7(Feb):429-454, 2006.
@article{kitzelmann/schmid:2006, author = {Emanuel Kitzelmann and Ute Schmid}, title = {Inductive Synthesis of Functional Programs: An Explanation Based Generalization Approach}, journal = {Journal of Machine Learning Research}, year = 2006, volume = 7, number = {Feb}, pages = {429--454}, address = {Cambridge, MA, USA}, publisher = {MIT Press}, issn = {1533-7928}, url = {http://jmlr.csail.mit.edu/papers/v7/kitzelmann06a.html}, keywords = {analytical ip; article; ebg; ifp; igor1; induction; inductive programming; program synthesis; recursive program schemes}, annote = {Inductive Synthesis of Functional Programs: An Explanation Based Generalization Approach}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/publications/JMLR-05-164-1.pdf}, abstract = {We describe an approach to the inductive synthesis of recursive equations from input/output-examples which is based on the classical two-step approach to induction of functional Lisp programs of Summers (1977). In a first step, I/O-examples are rewritten to traces which explain the outputs given the respective inputs based on a datatype theory. These traces can be integrated into one conditional expression which represents a non-recursive program. In a second step, this initial program term is generalized into recursive equations by searching for syntactical regularities in the term. Our approach extends the classical work in several aspects. The most important extensions are that we are able to induce a set of recursive equations in one synthesizing step, the equations may contain more than one recursive call, and additionally needed parameters are automatically introduced.} }
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Emanuel Kitzelmann and Ute Schmid.
Induction of functional programs based on relations between
Input/Output examples.
In C. Freksa, M. Kohlhase, and K. Schill, editors, KI'06:
Proceedings of 29th Annual German Conference on Artificial Intelligence
(Bremen, June14-19, 2006), 2006.
Poster Abstract.
@inproceedings{kitzelmann/schmid:2006b, author = {Emanuel Kitzelmann and Ute Schmid}, title = {Induction of Functional Programs based on Relations between {Input/Output} Examples}, editor = {C. Freksa and M. Kohlhase and K. Schill}, booktitle = {{KI'06}: Proceedings of 29th Annual German Conference on Artificial Intelligence (Bremen, June\,14--19, 2006)}, year = 2006, note = {Poster Abstract}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/publications/ki06extabst.pdf}, keywords = {2006; automatic programming; constructor systems; extended abstract; functional programming; igor2; induction; inductive; inductive functional programming; inductive inference; inductive program synthesis; inductive programming; myown; programming} }
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Emanuel Kitzelmann and Ute Schmid.
Inducing constructor systems from example-terms by detecting
syntactical regularities.
In M. Fernández and R. Lämmel, editors, RULE'06:
Proceedings of the 7th International Workshop on Rule Based Programming
(Seattle, USA, Aug.11, 2006), volume 174 of Electronic Notes in
Theoretical Computer Science, pages 49-63, Essex, UK, April 2007. Elsevier
Science Publishers Ltd.
@inproceedings{kitzelmann/schmid:2007, author = {Emanuel Kitzelmann and Ute Schmid}, title = {Inducing Constructor Systems from Example-Terms by Detecting Syntactical Regularities}, editor = {M. Fern{\'a}ndez and R. L{\"a}mmel}, booktitle = {{RULE'06}: Proceedings of the 7th International Workshop on Rule Based Programming (Seattle, USA, Aug.\,11, 2006)}, year = 2007, series = {Electronic Notes in Theoretical Computer Science}, volume = 174, pages = {49--63}, address = {Essex, UK}, month = {April}, publisher = {Elsevier Science Publishers Ltd.}, number = 1, url = {http://dx.doi.org/10.1016/j.entcs.2006.11.015}, abstract = {We present a technique for inducing functional programs from few, well chosen input/output-examples (I/O-examples). Potential applications for automatic program or algorithm induction are to enable end users to create their own simple programs, to assist professional programmers, or to automatically invent completely new and efficient algorithms. In our approach, functional programs are represented as constructor term rewriting systems (CSs) containing recursive rules. I/O-examples for a target function to be implemented are a set of pairs of terms (F(i_i),o_i) meaning that F(i_i)---denoting application of function F to input i_i---is rewritten to o_i by a CS implementing the function F. Induction is based on detecting syntactic regularities between example terms. In this paper we present theoretical results and describe an algorithm for inducing CSs over arbitrary signatures/data types which consist of one function defined by an arbitrary number of rules with an arbitrary number of non-nested recursive calls in each rule. Moreover, we present empirical results based on a prototypical implementation.}, annote = {ScienceDirect - Electronic Notes in Theoretical Computer Science : Inducing Constructor Systems from Example-Terms by Detecting Syntactical Regularities}, keywords = {2007; article; automatic programming; constructor systems; functional programming; igor2; induction; inductive; inductive inference; inductive program synthesis; inductive programming; myown; programming; published; rule-based programming}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/publications/rule06.pdf} }
-
Emanuel Kitzelmann and Ute Schmid, editors.
AAIP'07: Proceedings of the 2nd Workshop on Approaches and
Applications of Inductive Programming (Warsaw, Poland, Sep.17, 2007, 2007.
In conjunction with the 18th European Conference on Machine Learning
(ECML).
@proceedings{kitzelmann/schmid:2007b, title = {{AAIP'07}: Proceedings of the 2nd Workshop on Approaches and Applications of Inductive Programming (Warsaw, Poland, Sep.\,17, 2007}, year = 2007, editor = {Emanuel Kitzelmann and Ute Schmid}, note = {In conjunction with the 18th European Conference on Machine Learning ({ECML})}, keywords = {2007; automatic programming; induction; inductive program synthesis; inductive programming; machine learning; proceedings; programming; }, url = {http://www.cogsys.wiai.uni-bamberg.de/aaip07/}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/aaip07/aaip_print.pdf}, size = {59 pages} }
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Emanuel Kitzelmann.
Grundlegende Ansätze zur Induktiven Synthese Funktionaler
Programme (Summers und Biermann).
Kitzelmann, 2001.
@unpublished{kitzelmann:2001, author = {Emanuel Kitzelmann}, title = {{Grundlegende Ans{\"a}tze zur Induktiven Synthese Funktionaler Programme (Summers und Biermann)}}, year = 2001, note = {Kitzelmann}, keywords = {2001; automatic programming; functional programming; induction; inductive; inductive functional programming; inductive inference; inductive program synthesis; inductive programming; myown; programming; term paper}, school = {{Technische Universit{\"a}t Berlin}} }
-
Emanuel Kitzelmann.
Inductive functional program synthesis - a term-construction and
folding approach.
Diplomarbeit, Technische Universität Berlin, 2003.
Unpublished.
@mastersthesis{kitzelmann:2003, author = {Emanuel Kitzelmann}, title = {Inductive Functional Program Synthesis -- A Term-Construction and Folding Approach}, school = {{Technische Universit{\"a}t Berlin}}, year = 2003, type = {Diplomarbeit}, note = {Unpublished}, keywords = {analytical ip; ifp; igor1; induction; inductive programming; mastersthesis; program synthesis; recursive program schemes}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/kitzelmann/documents/thesis.ps} }
-
Ute Kitzelmann, Emanuel an Schmid.
An ebg approach to the inductive synthesis of functional programs.
In Luc De Raedt and Stefan Wrobel, editors, ICML'05:
Proceedings of the 22nd International Conference on Machine Learning (Bonn,
Germany, Aug.7-11, 2005), volume 119 of ACM International
Conference Proceeding Series, pages 15-26. ACM, 2005.
@inproceedings{kitzelmann:2005, author = {Kitzelmann, Emanuel an Schmid, Ute}, title = {An EBG Approach to the Inductive Synthesis of Functional Programs}, editor = {De~Raedt, Luc and Wrobel, Stefan}, booktitle = {{ICML'05}: Proceedings of the 22nd International Conference on Machine Learning (Bonn, Germany, Aug.\,7--11, 2005)}, year = 2005, series = {{ACM} International Conference Proceeding Series}, volume = 119, pages = {15--26}, publisher = {{ACM}}, isbn = {1-59593-180-5} }
-
Emanuel Kitzelmann.
Data-driven induction of recursive functions from
Inpuit/Output-examples.
In Emanuel Kitzelmann and Ute Schmid, editors, AAIP'07:
Proceedings of the 2nd Workshop on Approaches and Applications of Inductive
Programming (Warsaw, Poland, September17, 2007), pages 15-26, 2007.
Full Paper.
@inproceedings{kitzelmann:2007, author = {Emanuel Kitzelmann}, title = {Data-Driven Induction of Recursive Functions from {Inpuit/Output}-Examples}, editor = {Emanuel Kitzelmann and Ute Schmid}, booktitle = {{AAIP'07}: Proceedings of the 2nd Workshop on Approaches and Applications of Inductive Programming (Warsaw, Poland, September\,17, 2007)}, year = 2007, pages = {15--26}, note = {Full Paper}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/publications/aaip07.pdf}, url = {http://www.cogsys.wiai.uni-bamberg.de/aaip07/}, keywords = {2007; automatic programming; constructor systems; functional programming; igor2; induction; inductive functional programming; inductive program synthesis; inductive programming; inproceedings; programming; } }
-
Emanuel Kitzelmann.
Data-driven learning of functions over algebraic datatypes from
Input/Output-examples.
In Peter Geibel and Brijnesh J. Jain, editors, LNVD'07:
Learning from Non-Vectorial Data. Proceedings of the KI'07 Workshop,
Osnabrück, Germany, Sept.10, 2007, volume 6 of Publications of the
Institute of Cognitive Science, pages 36-45. Institute of Cognitive
Science, Universität Osnabrück, 2007.
@inproceedings{kitzelmann:2007b, author = {Emanuel Kitzelmann}, title = {Data-Driven Learning of Functions over Algebraic Datatypes from {Input/Output}-Examples}, editor = {Peter Geibel and Brijnesh J. Jain}, booktitle = {{LNVD'07}: Learning from Non-Vectorial Data. Proceedings of the {KI'07} Workshop, Osnabr\"uck, Germany, Sept.\,10, 2007}, year = 2007, series = {Publications of the Institute of Cognitive Science}, volume = 6, pages = {36--45}, publisher = {Institute of Cognitive Science, {Universit{\"a}t Osnabr{\"u}ck}}, keywords = {igor2; inductive programming}, abstract = {We describe a technique for inducing recursive functional programs over algebraic datatypes from few non-recursive and only positive ground example-equations. Induction is data-driven and based onstructural regularities between example terms. In our approach, functional programs are represented as constructor term rewriting systems containing recursive rewrite rules. In addition to the examples for the target functions, background knowledge functions that may be called by the induced functions can be given in form of ground equations. Our algorithm induces several dependent recursive target functions over arbitrary user-defined algebraic datatypes in one step and automatically introduces auxiliary subfunctions if needed. We have implemented a prototype of the described method and applied it to a number of problems.}, documenturl = {http://www.cogsci.uni-osnabrueck.de/cogsci/dirs/dynamic/publications/PICSvol6_2007.pdf} }
-
Emanuel Kitzelmann.
Analytical inductive functional programming.
In Michael Hanus, editor, LOPSTR'08: Pre-Proceedings of the
18th International Symposium on Logic-Based Program Synthesis and
Transformation (Valencia, Spain, July17-18, 2008), pages 166-180, 2008.
@inproceedings{kitzelmann:2008, author = {Emanuel Kitzelmann}, title = {Analytical Inductive Functional Programming}, editor = {Michael Hanus}, booktitle = {{LOPSTR'08}: Pre-Proceedings of the 18th International Symposium on Logic-Based Program Synthesis and Transformation (Valencia, Spain, July\,17--18, 2008)}, year = 2008, pages = {166--180}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/publications/lopstr08pre.pdf} }
-
Emanuel Kitzelmann.
Data-driven induction of functional programs.
In Malik Ghallab, Constantine D. Spyropoulos, Nikos Fakotakis, and
Nikos Avouris, editors, ECAI'08: Proceedings of the 18th European
Conference on Artificial Intelligence (Patras, Greece, July21-25, 2008),
volume 178 of Frontiers in Artificial Intelligence and Applications,
pages 781-782, Amsterdam, Netherlands, 2008. IOS Press.
@inproceedings{kitzelmann:2008b, author = {Emanuel Kitzelmann}, title = {Data-Driven Induction of Functional Programs}, editor = {Malik Ghallab and Constantine D. Spyropoulos and Nikos Fakotakis and Nikos Avouris}, booktitle = {{ECAI'08}: Proceedings of the 18th European Conference on Artificial Intelligence (Patras, Greece, July\,21--25, 2008)}, year = 2008, series = {Frontiers in Artificial Intelligence and Applications}, volume = 178, pages = {781--782}, address = {Amsterdam, Netherlands}, publisher = {IOS Press}, isbn = {978-960-6843-17-4}, keywords = {analytical ip; constructor systems; extended abstract; ifp; igor2; induction; inductive programming; inproceedings; program synthesis}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/publications/ecai08.pdf} }
-
Emanuel Kitzelmann.
Analytical inductive functional programming.
In Michael Hanus, editor, Logic-Based Program Synthesis and
Transformation. 18th International Symposium, LOPSTR'08, Valencia, Spain,
July17-18, 2008. Revised Selected Papers, volume 5438 of Lecture
Notes in Computer Science, pages 87-102, Berlin/Heidelberg, 2009.
Springer.
@inproceedings{kitzelmann:2009, author = {Emanuel Kitzelmann}, title = {Analytical Inductive Functional Programming}, editor = {Michael Hanus}, booktitle = { Logic-Based Program Synthesis and Transformation. 18th International Symposium, {LOPSTR'08}, Valencia, Spain, July\,17--18, 2008. Revised Selected Papers}, year = 2009, series = {Lecture Notes in Computer Science}, volume = 5438, pages = {87--102}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-642-00514-5}, url = {http://www.springerlink.com/content/9lv2308431533337/}, abstract = {We describe a new method to induce functional programs from small sets of non-recursive equations representing a subset of their input-output behaviour. Classical attempts to construct functionalLispprograms from input/output-examples areanalytical, i.e., aLispprogram belonging to a strongly restricted program class is algorithmically derived from examples. More recent approaches enumerate candidate programs and onlytestthem against the examples until a program which correctly computes the examples is found. Theoretically, large program classes can be induced generate-and-test based, yet this approach suffers from combinatorial explosion. We propose a combination of search and analytical techniques. The method described in this paper is search based in order to avoid strong a-priori restrictions as imposed by the classical analytical approach. Yet candidate programs are computed based on analytical techniques from the examples instead of being generated independently from the examples. A prototypical implementation shows first that programs are inducible which are not in scope of classical purely analytical techniques and second that the induction times are shorter than in recent generate-and-test based methods.}, doi = {10.1007/978-3-642-00515-2_7}, keywords = {analytical ip; constructor systems; ifp; igor2g; induction; inductive programming; inproceedings; program synthesis}, annote = {first regularly published paper on {Igor2.2}}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/publications/lopstr08.pdf} }
-
Emanuel Kitzelmann.
Inductive reasoning operators in the program synthesis system
Igor2.
Submitted to Logic-based Program Synthesis and Transformation
(LOPSTR'09, 19th International Symposium, Coimbra, Portugal, Sept.2009),
2009.
@unpublished{kitzelmann:2009b, author = {Emanuel Kitzelmann}, title = {Inductive Reasoning Operators in the Program Synthesis System {Igor2}}, year = 2009, note = {Submitted to Logic-based Program Synthesis and Transformation ({LOPSTR'09}, 19th International Symposium, Coimbra, Portugal, Sept.\,2009)}, keywords = {inductive programming}, annote = {add on to ``Analytical Inductive Functional Programming'' (http://www.cogsys.wiai.uni-bamberg.de/publications/lopstr08pre.pdf))} }
-
Emanuel Kitzelmann.
Inductive programming: A survey of program synthesis techniques.
In Ute Schmid, Emanuel Kitzelmann, and Rinus Plasmeijer, editors,
Approaches and Applications of Inductive Programming. 3rd International
Workshop, AAIP'09, Edinburgh, UK, Sept.4, 2009. Revised Papers, volume
5812 of Lecture Notes in Computer Science, pages 50-73,
Berlin/Heidelberg, 2010. Springer.
@inproceedings{kitzelmann:2010, author = {Emanuel Kitzelmann}, title = {Inductive Programming: A Survey of Program Synthesis Techniques}, editor = {Ute Schmid and Emanuel Kitzelmann and Rinus Plasmeijer}, booktitle = {Approaches and Applications of Inductive Programming. 3rd International Workshop, {AAIP'09}, Edinburgh, UK, Sept.\,4, 2009. Revised Papers}, year = 2010, series = {Lecture Notes in Computer Science}, volume = 5812, pages = {50--73}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-642-11930-9}, url = {http://www.springerlink.com/content/740664m804634k04/}, abstract = {Inductive programming (IP)the use of inductive reasoning methods for programming, algorithm design, and software developmentis a currently emerging research field. A major subfield is inductive program synthesis, the (semi-)automatic construction of programs from exemplary behavior. Inductive program synthesis is not a unified research field until today but scattered over several different established research fields such as machine learning, inductive logic programming, genetic programming, and functional programming. This impedes an exchange of theory and techniques and, as a consequence, a progress of inductive programming. In this paper we survey theoretical results and methods of inductive program synthesis that have been developed in different research fields until today.}, keywords = {inductive programming}, doi = {10.1007/978-3-642-11931-6_3}, documenturl = {http://www.springerlink.com/content/740664m804634k04/fulltext.pdf} }
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Emanuel Kitzelmann, Ute Schmid, Martin Mühlpfordt, and Fritz Wysotzki.
Folding of finite program terms to recursive program schemes.
In T. Sadam and V. Sgure, editors, Intelligent Systems.
Proceedings of the 1st International IEEE Symposium (Varna, Bulgaria,
Sept.10-12, 2002), volume 1, pages 144-149. IEEE Press, 2002.
@inproceedings{kitzelmann_ea:2002, author = {Emanuel Kitzelmann and Ute Schmid and Martin M{\"u}hlpfordt and Fritz Wysotzki}, title = {Folding of finite program terms to recursive program schemes}, editor = {T. Sadam and V. Sgure}, booktitle = {Intelligent Systems. Proceedings of the 1st International {IEEE} Symposium (Varna, Bulgaria, Sept.\,10--12, 2002)}, year = 2002, volume = 1, pages = {144--149}, publisher = {IEEE Press}, abstract = {We present an approach to inductive synthesis of functional programs based on the detection of recurrence relations. A given term is considered as the k-th unfolding of an unknown recursive program. If a recurrence relations can be identified in the term, it can be folded into a recursive program which: (a) can reproduce the term and (b) generalizes over it. Our approach goes beyond Summers' classical approach (1977) in several aspects: it is language independent and works for terms belonging to an arbitrary term algebra; it allows induction of sets of recursive equations which are in some arbitrary `calls' relation; induced equations can be dependent on more than one input parameters and we can detect interdependencies of variable substitutions in recursive calls; the given input terms can represent incomplete unfoldings of an hypothetical recursive program.}, annote = {Welcome to IEEE Xplore 2.0: Folding of finite program terms to recursive program schemes}, isbn = {0-7803-7134-8}, keywords = {2002; automatic programming; functional programming; igor1; induction; inductive; inductive functional programming; inductive inference; inductive program synthesis; inductive programming; inproceedings; myown; programming; published; recursive program schemes}, url = {http://dx.doi.org/10.1109/IS.2002.1044245} }
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Emanuel Kitzelmann, Ute Schmid, Martin Mühlpfordt, and Fritz Wysotzki.
Inductive synthesis of functional programs.
In J. Calmet, B. Benhamou, O. Caprotti, L. Henocque, and V. Sorge,
editors, Artificial Intelligence, Automated Reasoning, and Symbolic
Computation. Joint International Conferences AISC'02 and Calculemus'02,
Marseille, France, July1-5, 2002. Proceedings, volume 2385 of
Lecture Notes in Computer Science, pages 337-354, Berlin/Heidelberg,
2002. Springer.
@inproceedings{kitzelmann_ea:2002b, author = {Emanuel Kitzelmann and Ute Schmid and Martin M{\"u}hlpfordt and Fritz Wysotzki}, title = {Inductive Synthesis of Functional Programs}, editor = {Calmet, J. and Benhamou, B. and Caprotti, O. and Henocque, L. and Sorge, V.}, booktitle = {Artificial Intelligence, Automated Reasoning, and Symbolic Computation. Joint International Conferences {AISC'02} and {Calculemus'02}, Marseille, France, July\,1--5, 2002. Proceedings}, year = 2002, series = {Lecture Notes in Computer Science}, volume = 2385, pages = {337--354}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-43865-6}, url = {http://www.springerlink.com/content/r02frg6bh82g29pw/}, doi = {10.1007/3-540-45470-5_6}, abstract = {We present an approach to folding of finite program terms based on the detection of recurrence relations in a single given term which is considered as the k-th unfolding of an unknown recursive program. Our approach goes beyond Summers' classical approach in several aspects: It is language independent and works for terms belonging to an arbitrary term algebra; it allows induction of sets of recursive equations which are in some arbitrary ``calls'' relation; induced equations can be dependent on more than one input parameters and we can detect interdependencies of variable substitutions in recursive calls; the given input terms can represent incomplete unfoldings of an hypothetical recursive program.}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/publications/JMLR-05-164-1.pdf}, keywords = {2002; automatic programming; functional programming; igor1; induction; inductive; inductive functional programming; inductive inference; inductive program synthesis; inductive programming; inproceedings; myown; programming; published; recursive program schemes} }
-
Emanuel Kitzelmann, Roland J. Olsson, and Ute Schmid, editors.
AAIP'05: Proceedings of the 1st Workshop on Approaches and
Applications of Inductive Programming (Bonn, Germany, Aug.7, 2005), 2005.
In conjunction with the 22nd International Conference on Machine
Learning (ICML'05).
@proceedings{kitzelmann_ea:2005, title = {{AAIP'05}: Proceedings of the 1st Workshop on Approaches and Applications of Inductive Programming (Bonn, Germany, Aug.\,7, 2005)}, year = 2005, editor = {Emanuel Kitzelmann and Roland J. Olsson and Ute Schmid}, note = {In conjunction with the 22nd International Conference on Machine Learning ({ICML'05})}, url = {http://www.cogsys.wiai.uni-bamberg.de/aaip05/index.html}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/aaip05/proceedings/proceedings.pdf}, size = {81 pages} }
-
Timo Knuutila and Magnus Steinby.
The inference of tree languages from finite samples: an algebraic
approach.
Theoretical Computer Science, 129(2):337-367, 1994.
@article{knuutila/steinby:1994, author = {Timo Knuutila and Magnus Steinby}, title = {The inference of tree languages from finite samples: an algebraic approach}, journal = {Theoretical Computer Science}, year = 1994, volume = 129, number = 2, pages = {337--367} }
-
Yves Kodratoff and J. Fargues.
A sane algorithm for the synthesis of LISP functions from example
problems: The Boyer and Moore algorithm.
In Derek H. Sleeman, editor, Proceedings of AISB/GI
Conference (Hamburg, Germany, July 18-20, 1978, pages 169-175. Leeds
University, 1978.
Now ECAI: Proceedings of the 4th European Conference on Artificial
Intelligence.
@inproceedings{kodratoff/fargues:1978, author = {Yves Kodratoff and J. Fargues}, title = {A Sane Algorithm for the Synthesis of {LISP} Functions from Example Problems: The {Boyer} and {Moore} Algorithm}, editor = {Derek H. Sleeman}, booktitle = {Proceedings of {AISB}/{GI} Conference (Hamburg, Germany, July \,18--20, 1978}, year = 1978, pages = {169--175}, publisher = {Leeds University}, note = {Now {ECAI}: Proceedings of the 4th European Conference on Artificial Intelligence}, keywords = {analytical ip; ifp; induction; inductive programming; lisp; program synthesis} }
-
Yves Kodratoff.
A class of functions synthesized from a finite number of examples and
a LISP program scheme.
International Journal of Parallel Programming, 8(6):489-521,
December 1979.
@article{kodratoff:1979, author = {Yves Kodratoff}, title = {A Class of Functions Synthesized from a Finite Number of Examples and a {LISP} Program Scheme}, journal = {International Journal of Parallel Programming}, year = 1979, volume = 8, number = 6, pages = {489--521}, month = {December}, publisher = {Springer}, address = {Netherlands}, issn = {0885-7458 (Print) 1573-7640 (Online)}, url = {http://www.springerlink.com/content/x05l288304g8vk94/}, doi = {10.1007/BF00995500}, keywords = {Difference equation; fixed point semantics; generalization; instantiation (giving a particular value to the variables of a program scheme); Lisp programs; pattern matching; program proof; program synthesis}, abstract = {We define a class of functions that can be synthesized from example problems. The algorithmic representation of these functions is the interpretation of a given scheme. The instantiation of the scheme variables is realized by a new method which uses pattern matching then if necessary generalization and further pattern matching. One can compute the number of examples necessary to characterize in a unique way a function of this class.} }
-
Yves Kodratoff, Marta Franova, and Derek Partridge.
Why and how program synthesis?
In Klaus P. Jantke, editor, Analogical and Inductive Inference.
International Workshop AII'89, Reinhardsbrunn Castle, GDR, Oct.1-6,
1989. Proceedings, volume 397 of Lecture Notes in Computer Science,
pages 45-59, Berlin/Heidelberg, 1989. Springer.
@inproceedings{kodratoff_ea:1989, author = {Yves Kodratoff and Marta Franova and Derek Partridge}, title = {Why and how program synthesis?}, editor = {Jantke, Klaus P.}, booktitle = {Analogical and Inductive Inference. International Workshop {AII'89}, Reinhardsbrunn Castle, GDR, Oct.\,1--6, 1989. Proceedings}, year = 1989, series = {Lecture Notes in Computer Science}, volume = 397, pages = {45--59}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-51734-4}, url = {http://www.springerlink.com/content/78877816912005t8/}, abstract = {Among the several misunderstandings about Program Synthesis (PS), we particularly examine the one relative to Logic Programming alleged to have solve this problem. Even though theoretical reasons are well-known, we provide a detailed analysis of the practical reasons why a formal specification may be hard to program in PROLOG. All that contributes to the clarification of the exact role of PS in AI and in Software Engineering, and its possible application to software certification.}, keywords = {program synthesis from formal specifications; inductive theorem proving; certification cycle}, doi = {10.1007/3-540-51734-0_51}, annote = {ute-inflit} }
-
Pieter W. M. Koopman and Rinus Plasmeijer.
Generic generation of the elements of data types.
In Marko C. J. D. van Eekelen, editor, TFP'05: Revised
Selected Papers from the 6th Symposium on Trends in Functional Programming
(Tallinn, Estonia, Sep.23-24, 2005), volume 6 of Trends in
Functional Programming, pages 163-178. Intellect, 2007.
@inproceedings{koopman/plasmeijer:2007, author = {Pieter W. M. Koopman and Rinus Plasmeijer}, title = {Generic generation of the elements of data types}, editor = {Marko C. J. D. van Eekelen}, booktitle = {{TFP'05}: Revised Selected Papers from the 6th Symposium on Trends in Functional Programming (Tallinn, Estonia, Sep.\,23--24, 2005)}, year = 2007, series = {Trends in Functional Programming}, volume = 6, pages = {163--178}, publisher = {Intellect}, isbn = {978-1-84150-176-5} }
-
Pieter W. M. Koopman and Rinus Plasmeijer.
Systematic synthesis of functions.
In Henrik Nilsson, editor, TFP'06: Revised Selected Papers
from the 7th Symposium on Trends in Functional Programming (Nottingham,
United Kingdom, April19-21, 2006, volume 7 of Trends in Functional
Programming, pages 35-54. Intellect, 2007.
@inproceedings{koopman/plasmeijer:2007b, author = {Pieter W. M. Koopman and Rinus Plasmeijer}, title = {Systematic Synthesis of Functions}, editor = {Henrik Nilsson}, booktitle = {{TFP'06}: Revised Selected Papers from the 7th Symposium on Trends in Functional Programming (Nottingham, United Kingdom, April\,19--21, 2006}, year = 2007, series = {Trends in Functional Programming}, volume = 7, pages = {35--54}, publisher = {Intellect}, isbn = {978-1-84150-188-8}, documenturl = {http://www.cs.nott.ac.uk/~nhn/TFP2006/Papers/13-KoopmanPlasmeijer-SystematicSynthesisOfFunctions.pdf}, keywords = {automated testing; enumerative ip; ifp; induction; inductive programming; inproceedings; program synthesis} }
-
Pieter Koopman and Rinus Plasmeijer.
Synthesis of functions using generic programming.
In Ute Schmid, Emanuel Kitzelmann, and Rinus Plasmeijer, editors,
Approaches and Applications of Inductive Programming. 3rd International
Workshop, AAIP'09, Edinburgh, UK, Sept.4, 2009. Revised Papers, volume
5812 of Lecture Notes in Computer Science, pages 25-49,
Berlin/Heidelberg, 2010. Springer.
@inproceedings{koopman/plasmeijer:2010, author = {Pieter Koopman and Rinus Plasmeijer}, title = {Synthesis of Functions Using Generic Programming}, editor = {Ute Schmid and Emanuel Kitzelmann and Rinus Plasmeijer}, booktitle = {Approaches and Applications of Inductive Programming. 3rd International Workshop, {AAIP'09}, Edinburgh, UK, Sept.\,4, 2009. Revised Papers}, year = 2010, series = {Lecture Notes in Computer Science}, volume = 5812, pages = {25--49}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-642-11930-9}, url = {http://www.springerlink.com/content/g532p3m741r10373/}, abstract = {This paper describes a very flexible way to synthesize functions matching a given predicate. This can be used to find general recursive functions or}, doi = {10.1007/978-3-642-11931-6_2}, keywords = {gast; inductive programming}, documenturl = {http://www.springerlink.com/content/g532p3m741r10373/fulltext.pdf} }
-
Pieter Koopman, Artem Alimarine, Jan Tretmans, and Rinus Plasmeijer.
GAST: Generic automated software testing.
In Implementation of Functional Languages. 14th International
Workshop, IFL'02, Madrid, Spain, Sept.16-18, 2002. Revised Selected
Papers, volume 2670 of Lecture Notes in Computer Science, pages
84-100, Berlin/Heidelberg, 2003. Springer.
@inproceedings{koopman_ea:2003, author = {Pieter Koopman and Artem Alimarine and Jan Tretmans and Rinus Plasmeijer}, title = {{GAST}: Generic Automated Software Testing}, booktitle = {Implementation of Functional Languages. 14th International Workshop, {IFL'02}, Madrid, Spain, Sept.\,16--18, 2002. Revised Selected Papers}, year = 2003, series = {Lecture Notes in Computer Science}, volume = 2670, pages = {84--100}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-40190-2}, url = {http://www.springerlink.com/content/tt9u30x8wdal4d41/}, doi = {10.1007/3-540-44854-3_6}, keywords = {ase; automated testing; gast; software engineering; theorem proving}, abstract = {Software testing is a labor-intensive, and hence expensive, yet heavily used technique to control quality. In this paper we introduce Gast, a fully automatic test tool. Properties about functions and datatypes can be expressed in first order logic. Gast automaticallyand systematically generates appropriate test data, evaluates the property for these values, and analyzes the test results.This makes it easier and cheaper to test software components. The distinguishing property of our system is that the test dataare generated in a systematic and generic way using generic programming techniques. This implies that there is no need forthe user to indicate how data should be generated. Moreover, duplicated tests are avoided, and for finite domains Gast isable to prove a property by testing it for all possible values. As an important side-effect, it also encourages stating formalproperties of the software.} }
-
Richard E. Korf.
Macro-operators: A weak method for learning.
Artificial Intelligence, 26(1):35-77, 1985.
@article{korf:1985, author = {Richard E. Korf}, title = {Macro-Operators: A Weak Method for Learning}, journal = {Artificial Intelligence}, year = 1985, volume = 26, number = 1, pages = {35--77}, keywords = {macro-operators} }
-
John R. Koza.
Genetic Programming: On the Programming of Computers by Means
of Natural Selection.
MIT Press, Cambridge, MA, USA, 1992.
@book{koza:1992, author = {John R. Koza}, title = {Genetic Programming: {O}n the Programming of Computers by Means of Natural Selection}, publisher = {MIT Press}, year = 1992, address = {Cambridge, MA, USA}, keywords = {enumerative ip; gp; induction; inductive programming; program evolution; program synthesis}, isbn = {0-262-11170-5} }
-
John R. Koza, David Andre, Forrest H. Bennett, and Martin A. Keane.
Genetic Programming III: Darwinian Invention & Problem
Solving.
Morgan Kaufmann, San Francisco, CA, USA, 1999.
@book{koza_ea:1999, author = {John R. Koza and David Andre and Forrest H. Bennett and Martin A. Keane}, title = {Genetic Programming III: Darwinian Invention \& Problem Solving}, publisher = {Morgan Kaufmann}, year = 1999, address = {San Francisco, CA, USA}, keywords = {adr; enumerative ip; gp; induction; inductive programming; program evolution; program synthesis}, isbn = {1558605436} }
-
J. Krems, Ute Schmid, and Fritz Wysotzki, editors.
ECCM'96: Proceedings of the 1st European Workshop on Cognitive
Modelling (Berlin, Germany, Nov.14-16, 1996), volume 96 of
Forschungsberichte des Fachbereichs Informatik, TU Berlin, 1996.
@proceedings{krems_ea:1996, title = {{ECCM'96}: Proceedings of the 1st European Workshop on Cognitive Modelling (Berlin, Germany, Nov.\,14--16, 1996)}, year = 1996, editor = {J. Krems and Ute Schmid and Fritz Wysotzki}, volume = 96, number = 39, series = {Forschungsberichte des Fachbereichs Informatik}, address = {TU Berlin} }
-
R. L. Kruse.
On teaching recursion.
ACM SIGCCE-Bulletin, 14:92-96, 1982.
@article{kruse:1982, author = {R. L. Kruse}, title = {On teaching recursion}, journal = {{ACM} {SIGCCE}-Bulletin}, year = 1982, volume = 14, pages = {92--96} }
-
D. M. Kurland and R. D. Pea.
Children's mental models of recursive logo programs.
Journal of Educational Computing Research, 1(2):235-243, 1985.
@article{kurland/pea:1985, author = {D. M. Kurland and R. D. Pea}, title = {Children's Mental Models of Recursive Logo Programs}, journal = {Journal of Educational Computing Research}, year = 1985, volume = 1, number = 2, pages = {235--243} }
-
Steffen Lange.
A program synthesis algorithm exemplified.
In W. Bibel and K.P. Jantke, editors, Mathematical Methods of
Specification and Synthesis of Software Systems '85. Proceedings of the
International Spring School Wendisch-Rietz, GDR, April22-26, 1985, volume
215 of Lecture Notes in Computer Science, pages 185-193,
Berlin/Heidelberg, 1986. Springer.
@inproceedings{lange:1986, author = {Steffen Lange}, title = {A program synthesis algorithm exemplified}, editor = {W. Bibel and K.P. Jantke}, booktitle = {Mathematical Methods of Specification and Synthesis of Software Systems '85. Proceedings of the International Spring School Wendisch-Rietz, GDR, April\,22--26, 1985}, year = 1986, series = {Lecture Notes in Computer Science}, volume = 215, pages = {185--193}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-16444-9}, url = {http://www.springerlink.com/content/y7nl3x717553h736/}, abstract = {We present a algorithm for synthesizing programs from input/output examples of their behavior. This method is a prototype of a feasible inductive inference algorithm. It is able to synthesize programs from a considerably small number of examples, which, in fact, provide only incomplete information, in general. The main computational work performed during the synthesis process consists in deducations of term equations and inequalities. The investigated synthesis algorithm is well-structured and assumes some basic knowledge formalized as a heterogeneous signature with some first order axioms. We introduce this synthesis algorithm in detail by means of a particular program for a sorting algorithm.}, doi = {10.1007/3-540-16444-8_15} }
-
Pat Langley and Dongkyu Choi.
Learning recursive control programs from problem solving.
Journal of Machine Learning Research, 7:493-518, 2006.
Special Topic on Approaches and Applications of Inductive
Programming.
@article{langley/choi:2006, author = {Pat Langley and Dongkyu Choi}, title = {Learning Recursive Control Programs from Problem Solving}, journal = {Journal of Machine Learning Research}, year = 2006, volume = 7, pages = {493--518}, note = {Special Topic on Approaches and Applications of Inductive Programming}, publisher = {MIT Press}, editor = {Roland J. Olsson and Ute Schmid}, url = {http://jmlr.csail.mit.edu/papers/v7/}, documenturl = {http://www.jmlr.org/papers/volume7/langley06a/langley06a.pdf}, keywords = {inductive programming; learning-and-planning; planning; program synthesis; read} }
-
Stéphane Lapointe and Stan Matwin.
Sub-unification: a tool for efficient induction of recursive
programs.
In Derek Sleeman and Peter Edwards, editors, ML'92:
Proceedings of the Ninth International Workshop on Machine Learning
(Aberdeen, Scotland, United Kingdom, July1-3, 1992), pages 273-281, San
Francisco, CA, USA, 1992. Morgan Kaufmann.
@inproceedings{lapointe/matwin:1992, author = {St\'{e}phane Lapointe and Stan Matwin}, title = {Sub-unification: a Tool for Efficient Induction of Recursive Programs}, editor = {Derek Sleeman and Peter Edwards}, booktitle = {{ML'92}: Proceedings of the Ninth International Workshop on Machine Learning (Aberdeen, Scotland, United Kingdom, July\,1--3, 1992)}, year = 1992, pages = {273--281}, address = {San Francisco, CA, USA}, publisher = {Morgan Kaufmann}, url = {http://portal.acm.org/citation.cfm?id=141975.142038}, keywords = {CRUSTACEAN; analytical ip; ilp; inductive programming; ip-system; program synthesis; recursion}, annote = {sub-unification, a technique to invert implication} }
-
Stéphane Lapointe, Charles X. Ling, and Stan Matwin.
Constructive inductive logic programming.
In Ruzena Bajcsy, editor, IJCAI'93: Proceedings of the 13th
International Joint Conference on Artificial Intelligence (Chambéry,
France, Aug.28-Sep.3, 1993), pages 1030-1036. Morgan Kaufmann, 1993.
@inproceedings{lapointe_ea:1993, author = {St\'{e}phane Lapointe and Charles X. Ling and Stan Matwin}, title = {Constructive Inductive Logic Programming}, editor = {Ruzena Bajcsy}, booktitle = {{IJCAI}'93: Proceedings of the 13th International Joint Conference on Artificial Intelligence (Chamb\'ery, France, Aug.\,28--Sep.\,3, 1993)}, year = 1993, pages = {1030--1036}, publisher = {Morgan Kaufmann} }
-
N. Lavrač and S. Džeroski.
Inductive Logic Programming. Techniques and Applications.
Ellis Horwood, London, 1994.
@book{lavrac/dzeroski:1994, author = {N. Lavra\v{c} and S. D\v{z}eroski}, title = {Inductive Logic Programming. Techniques and Applications}, publisher = {Ellis Horwood}, year = 1994, address = {London}, annote = {ute-inflit} }
-
Guillaume Le Blanc.
Bmwk revisited generalization and formalization of an algorithm for
detecting recursive relations in term sequences.
In Machine Learning: ECML-94. European Conference on Machine
Learning Catania, Italy, April6-8, 1994. Proceedings, volume 784 of
Lecture Notes in Computer Science, pages 183-197, Berlin/Heidelberg,
1994. Springer.
@inproceedings{le-blanc:1994, author = {Le Blanc, Guillaume}, title = {BMWk revisited generalization and formalization of an algorithm for detecting recursive relations in term sequences}, booktitle = {Machine Learning: {ECML-94}. European Conference on Machine Learning Catania, Italy, April\,6--8, 1994. Proceedings}, year = 1994, series = {Lecture Notes in Computer Science}, volume = 784, pages = {183--197}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, abstract = {As several works in Machine Learning (particularly in Inductive Logic Programming) have focused on building recursive definitions from examples, this paper presents a formalization and a generalization of the BMWk methodology, which stems from program synthesis from examples, ten years ago. The framework of the proposed formalization is term rewriting. It allows to state some theoretical results on the qualities and limitations of the method.}, keywords = {analytical ip; ifp; induction; inductive programming; program synthesis; term rewriting}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-57868-0}, url = {http://www.springerlink.com/content/y0vv622028812821/}, doi = {10.1007/3-540-57868-4_58} }
-
G. Le Blanc.
BMWk revisited: Generalization and formalization of an algorithm
for detecting recursive relations in term sequences.
In Francesco Bergadano and Luc De Raedt, editors, Machine
Learning: ECML-94. European Conference on Machine Learning Catania, Italy,
April6-8, 1994. Proceedings, volume 784 of Lecture Notes in Computer
Science, pages 183-197, Berlin/Heidelberg, 1994. Springer.
@inproceedings{le-blanc:1994b, author = {G. {Le~Blanc}}, title = {{BMW}k revisited: {Generalization} and formalization of an algorithm for detecting recursive relations in term sequences}, editor = {Bergadano, Francesco and De~Raedt, Luc}, booktitle = {Machine Learning: {ECML-94}. European Conference on Machine Learning Catania, Italy, April\,6--8, 1994. Proceedings}, year = 1994, series = {Lecture Notes in Computer Science}, volume = 784, pages = {183--197}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-57868-0}, url = {http://www.springerlink.com/content/y0vv622028812821/}, abstract = {As several works in Machine Learning (particularly in Inductive Logic Programming) have focused on building recursive definitions from examples, this paper presents a formalization and a generalization of the BMWk methodology, which stems from program synthesis from examples, ten years ago. The framework of the proposed formalization is term rewriting. It allows to state some theoretical results on the qualities and limitations of the method.}, doi = {10.1007/3-540-57868-4_58}, annote = {ute-inflit} }
-
C. Leinbach and A.L. Wijesinha.
On classifying recursive algorithms.
ACM SIGCCE-Bulletin, 18:186-190, 1986.
@article{leinbach/wijesinha:1986, author = {C. Leinbach and A.L. Wijesinha}, title = {On classifying recursive algorithms}, journal = {{ACM} {SIGCCE}-Bulletin}, year = 1986, volume = 18, pages = {186--190} }
-
Leonid A. Levin.
Universal sequential search problems.
Problems of Information Transmission, 9(3), 1973.
@article{levin:1973, author = {Leonid A. Levin}, title = {Universal Sequential Search Problems}, journal = {Problems of Information Transmission}, year = 1973, volume = 9, number = 3, keywords = {universal search} }
-
Xiang Li.
Utilising Restricted For-Loops in Genetic Programming.
PhD thesis, Royal Melbourne Institute of Technology, School of
Computer Science and Information Technology, Melbourne, Victoria, Australia,
2007.
@phdthesis{li:2007, author = {Xiang Li}, title = {Utilising Restricted For-Loops in Genetic Programming}, school = {Royal Melbourne Institute of Technology, School of Computer Science and Information Technology}, year = 2007, address = {Melbourne, Victoria, Australia}, documenturl = {http://goanna.cs.rmit.edu.au/~vc/papers/li-phd.pdf}, keywords = {enumerative ip; gp; induction; inductive programming; loops; program evolution; program synthesis} }
-
Henry Lieberman.
Programming descriptive analogies by example.
In Workshop on Inheritance Hierarchies in Knowledge
Representation (Viareggio, Italy, Feb.6-8, 1989), 1989.
@inproceedings{lieberman:1989, author = {Henry Lieberman}, title = {Programming Descriptive Analogies by Example}, booktitle = {Workshop on Inheritance Hierarchies in Knowledge Representation (Viareggio, Italy, Feb.\,6--8, 1989)}, year = 1989, annote = {ute-inflit} }
-
H. Lieberman.
Tinker: A programming by demonstration system for beginning
programmers.
In Alan Cypher, editor, Watch What I Do: Programming by
Demonstration, chapter 2. MIT Press, Cambridge, MA, 1993.
@incollection{lieberman:1993, author = {H. Lieberman}, title = {Tinker: {A} Programming by Demonstration System for Beginning Programmers}, editor = {Alan Cypher}, booktitle = {Watch What {I} Do: {Programming} by Demonstration}, publisher = {MIT Press}, year = 1993, chapter = 2, address = {Cambridge, MA}, documenturl = {http://www.acypher.com/wwid/Chapters/02Tinker.html}, annote = {ute-inflit} }
-
Henry Lieberman, editor.
Your Wish is My Command: Programming by Example.
Morgan Kaufmann, 2001.
@book{lieberman:2001, editor = {Henry Lieberman}, title = {Your Wish is My Command: Programming by Example}, publisher = {Morgan Kaufmann}, year = 2001, keywords = {pbe} }
-
Xiaofeng C. Ling.
Inductive learning from good examples.
In John Mylopoulos and Raymond Reiter, editors, IJCAI'91:
Proceedings of the 12th International Joint Conference on Artificial
Intelligence (Sydney, Australia, Aug.24-30, 1991), volume 2, pages
751-756. Morgan Kaufmann, 1991.
@inproceedings{ling:1991, author = {Xiaofeng C. Ling}, title = {Inductive Learning from Good Examples}, editor = {Mylopoulos, John and Reiter, Raymond}, booktitle = {{IJCAI}'91: Proceedings of the 12th International Joint Conference on Artificial Intelligence (Sydney, Australia, Aug.\,24--30, 1991)}, year = 1991, volume = 2, pages = {751--756}, publisher = {Morgan Kaufmann}, isbn = {1-55860-160-0}, url = {http://dli.iiit.ac.in/ijcai/IJCAI-91-VOL2/CONTENT/content.htm}, keywords = {ilp; inductive programming; learnability; machine learning; program synthesis; recursion} }
-
Moshe Looks.
Competent Program Evolution.
PhD thesis, Washington University in St. Louis, 2006.
@phdthesis{looks:2006, author = {Moshe Looks}, title = {Competent Program Evolution}, school = {Washington University in St. Louis}, year = 2006, url = {http://metacog.org/doc.html}, keywords = {cognition; enumerative ip; experiment; induction; inductive programming; moses; program evolution; program synthesis} }
-
Moshe Looks.
Scalable estimation-of-distribution program evolution.
In Hod Lipson, editor, GECCO'07: Proceedings of the 9th Annual
Conference on Genetic and Evolutionary Computation (London, England, UK,
July7-11, 2007), pages 539-546, New York, NY, USA, 2007. ACM.
Session “Estimation of distribution algorithms”.
@inproceedings{looks:2007, author = {Moshe Looks}, title = {Scalable Estimation-of-Distribution Program Evolution}, editor = {Hod Lipson}, booktitle = {{GECCO'07}: Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation (London, England, UK, July\,7--11, 2007)}, year = 2007, pages = {539--546}, address = {New York, NY, USA}, publisher = {{ACM}}, note = {Session ``Estimation of distribution algorithms''}, isbn = {978-1-59593-697-4}, url = {http://doi.acm.org/10.1145/1276958.1277072}, keywords = {cognition; enumerative ip; induction; inductive programming; machine learning; moses; program evolution; program synthesis}, annote = {Scalable estimation-of-distribution program evolution} }
-
H. R. Lu and K. S. Fu.
Inferability of context-free programmed grammars.
International Journal of Computer and Information Sciences,
13(1):33-58, February 1984.
@article{lu/fu:1984, author = {H. R. Lu and K. S. Fu}, title = {Inferability of context-free programmed grammars}, journal = {International Journal of Computer and Information Sciences}, year = 1984, volume = 13, number = 1, pages = {33--58}, month = {February}, issn = {0091-7036}, keywords = {CFPG analysis; autocorrelation; context-free control description; diagram; grammars; grammatical inferability inference; language pattern programmed recognition; string syntactic} }
-
Haoru Lu and Ksun Fu.
A general approach to inference of context-free programmed grammars.
IEEE Transactions on Systems, Man, and Cybernetics,
14(2):191-202, 1984.
@article{lu/fu:1984b, author = {Haoru Lu and Ksun Fu}, title = {A General Approach to Inference of Context-Free Programmed Grammars}, journal = {IEEE Transactions on Systems, Man, and Cybernetics}, year = 1984, volume = 14, number = 2, pages = {191--202}, keywords = {language; matematics}, annote = {ute-inflit} }
-
Jianguo Lu and Jiafu Xu.
Analogical program derivation based on type theory.
Theoretical Computer Science, 113(2):259-272, June 1993.
@article{lu/xu:1993, author = {Jianguo Lu and Jiafu Xu}, title = {Analogical program derivation based on type theory}, journal = {Theoretical Computer Science}, year = 1993, volume = 113, number = 2, pages = {259--272}, month = {June}, day = 7, url = {http://dx.doi.org/10.1016/0304-3975(93)90004-D}, publisher = {Elsevier Science Publishers Ltd.}, address = {Essex, UK}, keywords = {analogical analogy derivation; development; formal matching method; program reasoning; specification; theory type; Programming and algorithm theory; Software engineering techniques}, issn = {0304-3975}, school = {Institute of Computer Software, Nanjing University, Nanjing 210008, People's Republic of China}, abstract = {Our goal is to develop a formal method for analogically deriving programs from past programming experience. It is commonly recognized that program development plays a central role in analogical programming. This paper proposes to use a calculus to uniformly represent specification, program, and the development from the former to the latter. Thus analogical reasoning can be discussed in a single framework. In this framework, we first propose an analogy matching method to seek the analogical correspondence between two specifications based on a generalization procedure. Secondly, the analogical correspondence is used as a basis for transforming existing program derivations to new ones. The corresponding program can be obtained by simple calculation of its type. Finally, an example is given to illustrate our method.} }
-
Donato Malerba.
Learning recursive theories in the normal ILP setting.
Fundamenta Informaticae, 57(1):39-77, 2003.
@article{malerba:2003, author = {Donato Malerba}, title = {Learning Recursive Theories in the Normal {ILP} Setting}, journal = {Fundamenta Informaticae}, year = 2003, volume = 57, number = 1, pages = {39--77}, address = {Amsterdam, The Netherlands}, publisher = {IOS Press}, issn = {0169-2968}, url = {http://portal.acm.org/citation.cfm?id=1221518}, keywords = {ATRE; ilp; inductive programming; ip-system; program synthesis; recursion}, abstract = {Induction of recursive theories in the normal ILP setting is a difficult learning task whose complexity is equivalent to multiple predicate learning. In this paper we propose computational solutions to some relevant issues raised by the multiple predicate learning problem. A separate-and-parallel-conquer search strategy is adopted to interleave the learning of clauses supplying predicates with mutually recursive definitions. A novel generality order to be imposed on the search space of clauses is investigated, in order to cope with recursion in a more suitable way. The consistency recovery is performed by reformulating the current theory and by applying a layering technique, based on the collapsed dependency graph. The proposed approach has been implemented in the ILP system ATRE and tested on some laboratory-sized and real-world data sets. Experimental results demonstrate that ATRE is able to learn correct theories autonomously and to discover concept dependencies. Finally, related works and their main differences with our approach are discussed.} }
-
Zohar Manna and Richard Waldinger.
Knowledge and reasoning in program synthesis.
Artificial Intelligence, 6:175-208, 1975.
@article{manna/waldinger:1975, author = {Manna, Zohar and Waldinger, Richard}, title = {Knowledge and reasoning in program synthesis}, journal = {Artificial Intelligence}, year = 1975, volume = 6, pages = {175--208} }
-
Zohar Manna and Richard Waldinger.
Synthesis: Dreams -> programs.
IEEE Transactions on Software Engineering, 5(4):294-328, 1979.
@article{manna/waldinger:1979, author = {Manna, Zohar and Waldinger, Richard}, title = {Synthesis: Dreams $\rightarrow$ Programs}, journal = {IEEE Transactions on Software Engineering}, year = 1979, volume = 5, number = 4, pages = {294--328} }
-
Zohar Manna and Richard Waldinger.
A deductive approach to program synthesis.
ACM Transactions on Programming Languages and Systems,
2(1):90-121, 1980.
@article{manna/waldinger:1980, author = {Manna, Zohar and Waldinger, Richard}, title = {A Deductive Approach to Program Synthesis}, journal = {{ACM} Transactions on Programming Languages and Systems}, year = 1980, volume = 2, number = 1, pages = {90--121}, address = {New York, NY, USA}, publisher = {{ACM}}, url = {http://doi.acm.org/10.1145/357084.357090}, keywords = {article; ase; deductive program synthesis; program synthesis}, abstract = {Program synthesis is the systematic derivation of a program from a given specification. A deductive approach to program synthesis is presented for the construction of recursive programs. This approach regards program synthesis as a theorem-proving task and relies on a theorem-proving method that combines the features of transformation rules, unification, and mathematical induction within a single framework.} }
-
Zohar Manna and Richard Waldinger.
How to clear a block: A theory of plans.
Journal of Automated Reasoning, 3(4):343-378, December 1987.
@article{manna/waldinger:1987, author = {Manna, Zohar and Waldinger, Richard}, title = {How to Clear a Block: A Theory of Plans}, journal = {Journal of Automated Reasoning}, year = 1987, volume = 3, number = 4, pages = {343--378}, month = {December}, publisher = {Kluwer Academic Publishers}, keywords = {planning} }
-
J. Marcinkowski and L. Pacholski.
Undecidability of the horn-clause implication problem.
In SFCS'92: Proceedings of the 33rd IEEE Annual Symposium on
Foundations of Computer Science (Pittsburgh, PA, USA, Oct.24-27, 1992),
pages 354-362. IEEE, 1992.
@inproceedings{marcinkowski/pacholski:1992, author = {J. Marcinkowski and L. Pacholski}, title = {Undecidability of the Horn-clause Implication Problem}, booktitle = {{SFCS'92}: Proceedings of the 33rd IEEE Annual Symposium on Foundations of Computer Science (Pittsburgh, PA, USA, Oct.\,24--27, 1992)}, year = 1992, pages = {354--362}, publisher = {IEEE}, doi = {10.1109/SFCS.1992.267755}, isbn = {0-8186-2900-2}, keywords = {decidability; horn-clauses; logic}, annote = {implication among Horn-clauses is not decidable}, documenturl = {http://www.computer.org/plugins/dl/pdf/proceedings/focs/1992/2900/00/0267755.pdf} }
-
Lionel Martin and Christel Vrain.
A three-valued framework for the induction of general logic programs.
In Luc De Raedt, editor, Advances in Inductive Logic
Programming. IOS Press, 1996.
@incollection{martin/vrain:1996, author = {Lionel Martin and Christel Vrain}, title = {A Three-valued Framework for the Induction of General Logic Programs}, editor = {De~Raedt, Luc}, booktitle = {Advances in Inductive Logic Programming}, publisher = {IOS Press}, year = 1996, keywords = {ICN; ilp; inductive programming; ip-system; program synthesis; recursion}, annote = {technique to deal with recursion: recursive dependencies} }
-
John McCarthy.
Recursive functions of symbolic expressions and their computation by
machine, part i.
Communications of the ACM, 3(4):184-195, 1960.
@article{mccarthy:1960, author = {John McCarthy}, title = {Recursive functions of symbolic expressions and their computation by machine, Part I}, journal = {Communications of the {ACM}}, year = 1960, volume = 3, number = 4, pages = {184--195}, address = {New York, NY, USA}, publisher = {{ACM}}, url = {http://doi.acm.org/10.1145/367177.367199}, documenturl = {http://portal.acm.org/ft_gateway.cfm?id=367199&type=pdf&coll=GUIDE&dl=GUIDE&CFID=96260185&CFTOKEN=23197999}, keywords = {lisp}, annote = {the original LISP paper} }
-
James McDonald and John Anton.
SPECWARE - producing software correct by construction.
Technical Report KES.U.01.3., Kestrel Institute, 2001.
@techreport{mcdonald/anton:2001, author = {James McDonald and John Anton}, title = {{SPECWARE} -- Producing Software Correct by Construction}, institution = {Kestrel Institute}, year = 2001, number = {KES.U.01.3.}, keywords = {ase; deductive program synthesis; kestrel; program synthesis; software engineering; specware; techreport} }
-
Erik Meijer, Maarten Fokkinga, and Ross Paterson.
Functional programming with bananas, lenses, envelopes and barbed
wire.
In Functional Programming Languages and Computer Architecture.
5th ACM Conference, Cambridge, MA, USA, Aug.26-30, 1991. Proceedings,
volume 523 of Lecture Notes in Computer Science, pages 124-144,
Berlin/Heidelberg, 1991. Springer.
@inproceedings{meijer_ea:1991, author = {Erik Meijer and Maarten Fokkinga and Ross Paterson}, title = {Functional Programming with Bananas, Lenses, Envelopes and Barbed Wire}, booktitle = {Functional Programming Languages and Computer Architecture. 5th {ACM} Conference, Cambridge, MA, USA, Aug.\,26--30, 1991. Proceedings}, year = 1991, series = {Lecture Notes in Computer Science}, volume = 523, pages = {124--144}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-54396-1}, url = {http://www.springerlink.com/content/77t3588175m4h5n7/}, doi = {10.1007/3540543961_7}, keywords = {catamorphisms; formal methods; functional programming; higher-order functions; programming; recursion theory; seminal paper}, abstract = {We develop a calculus for lazy functional programming based on recursion operators associated with data type definitions. For these operators we derive various algebraic laws that are useful in deriving and manipulating programs. We shall show that all example functions in Bird and Wadler's Introduction to Functional Programming can be expressed using these operators.} }
-
José Meseguer and Joseph A. Goguen.
Initiality, induction, and computability.
In Maurice Nivat and John C. Reynolds, editors, Algebraic
Methods in Semantics, pages 459-541. Cambridge University Press, 1986.
@incollection{meseguer/goguen:1986, author = {Jos{\'e} Meseguer and Joseph A. Goguen}, title = {Initiality, Induction, and Computability}, editor = {Maurice Nivat and John C. Reynolds}, booktitle = {Algebraic Methods in Semantics}, publisher = {Cambridge University Press}, year = 1986, pages = {459--541}, keywords = {algebraic specification; equational logic; term rewriting} }
-
Ryszard S. Michalski and Robert E. Stepp.
Learning from observation: Conceptual clustering.
In Ryszard S. Michalski, Jaime G. Carbonell, and Tom M. Mitchell,
editors, Machine Learning: An Artificial Intelligence Approach,
chapter 11, pages 331-364. Tioga, 1983.
@incollection{michalski/stepp:1983, author = {Ryszard S. Michalski and Robert E. Stepp}, title = {Learning From Observation: Conceptual Clustering}, editor = {Ryszard S. Michalski and Jaime G. Carbonell and Tom M. Mitchell}, booktitle = {Machine Learning: An Artificial Intelligence Approach}, publisher = {Tioga}, year = 1983, chapter = 11, pages = {331--364}, keywords = {constructive induction; machine learning} }
-
Tom M. Mitchell.
The need for biases in learning generalizations.
Technical report, Rutgers University, New Brunswick, NJ, 1980.
@techreport{mitchell:1980, author = {Tom M. Mitchell}, title = {The Need for Biases in Learning Generalizations}, institution = {Rutgers University}, year = 1980, address = {New Brunswick, NJ}, keywords = {machine learning} }
-
Tom M. Mitchell.
Generalization as search.
Artificial Intelligence, 18(2):203-226, 1982.
@article{mitchell:1982, author = {Tom M. Mitchell}, title = {Generalization as Search}, journal = {Artificial Intelligence}, year = 1982, volume = 18, number = 2, pages = {203--226}, editor = {Daniel G. Bobrow}, keywords = {machine learning; seminal paper}, url = {http://dx.doi.org/10.1016/0004-3702(82)90040-6}, abstract = {The problem of concept learning, or forming a general description of a class of objects given a set of examples and non-examples, is viewed here as a search problem. Existing programs that generalize from examples are characterized in terms of the classes of search strategies that they employ. Several classes of search strategies are then analyzed and compared in terms of their relative capabilities and computational complexities.} }
-
Thomas M. Mitchell.
Machine Learning.
McGraw-Hill, 1 edition, 1997.
@book{mitchell:1997, author = {Thomas M. Mitchell}, title = {Machine Learning}, publisher = {McGraw-Hill}, year = 1997, edition = 1, url = {http://www.cs.cmu.edu/~tom/mlbook.html}, keywords = {applications; book; induction; machine learning}, isbn = 0070428077 }
-
Neil Mitchell.
Deriving generic functions by example.
In Jan Tobias Mühlberg and Juan Ignacio Perna, editors,
Proceedings of the First York Doctoral Symposium 2007 (York, UK, Oct.26,
2007), pages 55-62. Department of Computer Science, University of York, UK,
2007.
TechReport YCS-2007-421.
@inproceedings{mitchell:2007, author = {Neil Mitchell}, title = {Deriving Generic Functions by Example}, editor = {Jan Tobias M\"{u}hlberg and Juan Ignacio Perna}, booktitle = {Proceedings of the First York Doctoral Symposium 2007 (York, UK, Oct.\,26, 2007)}, year = 2007, pages = {55--62}, publisher = {Department of Computer Science, University of York, UK}, note = {Tech\,Report YCS-2007-421}, documenturl = {http://community.haskell.org/~ndm/downloads/paper-deriving_generic_functions_by_example-26_oct_2007.pdf}, abstract = {A function is said to be generic if it operates over values of any data type. For example, a generic equality function can test pairs of booleans, integers, lists, trees etc. In most languages programmers must define generic functions multiple times, specialised for each data type. Alternatively, a tool could be used to specify the relationship between the data type and the implementation, but this relationship may be complex. This paper describes a solution: given a single example of the generic function on one data type, we can infer the relationship between a data type and the implementation. We have used our method in the Derive tool, allowing the implementation of 60\% of the generic functions to be inferred.} }
-
Neil Mitchell.
Deriving a relationship from a single example.
In Ute Schmid, Emanuel Kitzelmann, and Rinus Plasmeijer, editors,
Approaches and Applications of Inductive Programming. 3rd International
Workshop, AAIP'09, Edinburgh, UK, Sept.4, 2009. Revised Papers, volume
5812 of Lecture Notes in Computer Science, pages 1-24,
Berlin/Heidelberg, 2010. Springer.
@inproceedings{mitchell:2010, author = {Neil Mitchell}, title = {Deriving a Relationship from a Single Example}, editor = {Ute Schmid and Emanuel Kitzelmann and Rinus Plasmeijer}, booktitle = {Approaches and Applications of Inductive Programming. 3rd International Workshop, {AAIP'09}, Edinburgh, UK, Sept.\,4, 2009. Revised Papers}, year = 2010, series = {Lecture Notes in Computer Science}, volume = 5812, pages = {1--24}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-642-11930-9}, url = {http://www.springerlink.com/content/q764u283q955x810/}, abstract = {Given an appropriate domain specific language (DSL), it is possible to describe the relationship between Haskell data types and many generic functions, typically type-class instances. While describing the relationship is possible, it is not always an easy task. There is an alternative simply give one example output for a carefully chosen input, and have the relationship derived.}, doi = {10.1007/978-3-642-11931-6_1}, documenturl = {http://www.springerlink.com/content/q764u283q955x810/fulltext.pdf} }
-
Chowdhury R. Mofizur and Masayuki Numao.
Top-down induction of recursive programs from small number of sparse
examples.
In Luc De Raedt, editor, Advances in Inductive Logic
Programming. IOS Press, 1996.
@incollection{mofizur/numao:1996, author = {Chowdhury R. Mofizur and Masayuki Numao}, title = {Top-down Induction of Recursive Programs from Small Number of Sparse Examples}, editor = {De~Raedt, Luc}, booktitle = {Advances in Inductive Logic Programming}, publisher = {IOS Press}, year = 1996, keywords = {SMART; ilp; inductive programming; ip-system; program synthesis; recursion} }
-
Oleg Monakhov and Emilia Monakhova.
Synthesis of scientific algorithms based on evolutionary computation
and templates.
In Emanuel Kitzelmann, Roland J. Olsson, and Ute Schmid, editors,
AAIP'05: Proceedings of the 1st Workshop on Approaches and
Applications of Inductive Programming (Bonn, Germany, Aug.7, 2005), pages
29-35, 2005.
Full Paper.
@inproceedings{monakhov/monakhova:2005, author = {Oleg Monakhov and Emilia Monakhova}, title = {Synthesis of Scientific Algorithms based on Evolutionary Computation and Templates}, editor = {Emanuel Kitzelmann and Roland J. Olsson and Ute Schmid}, booktitle = {{AAIP'05}: Proceedings of the 1st Workshop on Approaches and Applications of Inductive Programming (Bonn, Germany, Aug.\,7, 2005)}, year = 2005, pages = {29--35}, note = {Full Paper}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/aaip05/proceedings/mon-ip32.pdf} }
-
Oleg Monakhov.
Evolutionary synthesis of algorithms based on templates.
Optoelectronics, Instrumentation and Data Processing, 2006.
@article{monakhov:2006, author = {Oleg Monakhov}, title = {Evolutionary synthesis of algorithms based on templates}, journal = {Optoelectronics, Instrumentation and Data Processing}, year = 2006, publisher = {Allerton Press, Inc. distributed exclusively by Springer Science+Business Media LLC}, issn = {8756-6990 (Print) 1934-7944 (Online)}, documenturl = {http://www.ict.nsc.ru/jct/getfile.php?id=775} }
-
David J. Montana.
Strongly typed genetic programming.
Evolutionary Compututation, 3(2):199-230, 1995.
@article{montana:1995, author = {David J. Montana}, title = {Strongly Typed Genetic Programming}, journal = {Evolutionary Compututation}, year = 1995, volume = 3, number = 2, pages = {199--230}, address = {Cambridge, MA, USA}, publisher = {MIT Press}, url = {http://dx.doi.org/10.1162/evco.1995.3.2.199}, keywords = {enumerative ip; gp; induction; inductive programming; program evolution; program synthesis}, abstract = {Genetic programming is a powerful method for automatically generating computer programs via the process of natural selection (Koza, 1992). However, in its standard form, there is no way to restrict the programs it generates to those where the functions operate on appropriate data types. In the case when the programs manipulate multiple data types and contain functions designed to operate on particular data types, this can lead to unnecessarily large search times and/or unnecessarily poor generalization performance. Strongly typed genetic programming (STGP) is an enhanced version of genetic programming that enforces data-type constraints and whose use of generic functions and generic data types makes it more powerful than other approaches to type-constraint enforcement. After describing its operation, we illustrate its use on problems in two domains, matrix/vector manipulation and list manipulation, which require its generality. The examples are (1) the multidimensional least-squares regression problem, (2) the multidimensional Kalman filter, (3) the list manipulation function NTH, and (4) the list manipulation function MAPCAR.} }
-
Martin Mühlpfordt and Ute Schmid.
Synthesis of recursive functions with interdependent parameters.
In S. Lange and T. Zeugmann, editors, ALT'98: Proceedings of
the satellite workshop on Applied Learning Theory (Kaiserslautern, Germany,
Oct.7, 1998, 1998.
Satellite workshop of the 9th International Conference on
Algorithmic Learning Theory (Kaiserslautern, Rheinland-Pfalz, Germany,
Oct.8-10, 1998).
@inproceedings{muehlpfordt/schmid:1998, author = {Martin M{\"u}hlpfordt and Ute Schmid}, title = {Synthesis of recursive functions with interdependent parameters}, editor = {Lange, S. and Zeugmann, T.}, booktitle = {{ALT'98}: Proceedings of the satellite workshop on Applied Learning Theory (Kaiserslautern, Germany, Oct.\,7, 1998}, year = 1998, note = {Satellite workshop of the 9th {International Conference on Algorithmic Learning Theory} (Kaiserslautern, Rheinland-Pfalz, Germany, Oct.\,8--10, 1998)} }
-
Martin Mühlpfordt and Ute Schmid.
Synthesis of recursive functions with interdependent parameters.
In FGML'98: Proceedings of the Annual Meeting of the GI
Machine Learning Group (Technische Universität, Berlin, Aug.17.-19,
1998), volume 98 of Forschungsberichte des Fachbereichs Informatik,
pages 132-139, TU Berlin, 1998.
Beiträge zum Treffen der GI-Fachgruppe 1.1.3 Maschinelles Lernen.
@inproceedings{muehlpfordt/schmid:1998b, author = {Martin M{\"u}hlpfordt and Ute Schmid}, title = {Synthesis of recursive functions with interdependent parameters}, booktitle = {{FGML'98}: Proceedings of the {Annual Meeting of the GI Machine Learning Group} (Technische Universit\"at, Berlin, Aug.\,17.--19, 1998)}, year = 1998, series = {Forschungsberichte des Fachbereichs Informatik}, volume = 98, pages = {132--139}, address = {TU Berlin}, note = {Beitr{\"a}ge zum Treffen der GI-Fachgruppe 1.1.3 Maschinelles Lernen}, number = 11 }
-
Martin Mühlpfordt.
Syntaktische Inferenz Rekursiver Programmschemata.
Diplomarbeit, Technische Universität Berlin, 2000.
@mastersthesis{muehlpfordt:2000, author = {Martin M\"{u}hlpfordt}, title = {{Syntaktische Inferenz Rekursiver Programmschemata}}, school = {Technische Universit\"{a}t Berlin}, year = 2000, type = {Diplomarbeit}, keywords = {igor1; inductive programming} }
-
M. Müller and Ute Schmid.
IPAL - a system that integrates problem solving, skill
acquisition, and learning by analogy.
In Ute Schmid, J. Krems, and Fritz Wysotzki, editors, ECCM'96:
Proceedings of the 1st European Workshop on Cognitive Modelling (Berlin,
Germany, Nov.14-16, 1996), volume 96 of Forschungsberichte des
Fachbereichs Informatik, pages 246-247, TU Berlin, 1996.
@inproceedings{mueller/schmid:1996, author = {M. M{\"u}ller and Ute Schmid}, title = {{IPAL} -- A system that integrates problem solving, skill acquisition, and learning by analogy}, editor = {Ute Schmid and J. Krems and Fritz Wysotzki}, booktitle = {{ECCM'96}: Proceedings of the 1st European Workshop on Cognitive Modelling (Berlin, Germany, Nov.\,14--16, 1996)}, year = 1996, series = {Forschungsberichte des Fachbereichs Informatik}, volume = 96, pages = {246--247}, address = {TU Berlin}, number = 39 }
-
Stephen H. Muggleton and Wray L. Buntine.
Machine invention of first-order predicates by inverting resolution.
In John E. Laird, editor, ICML'88: Proceedings of the 5th
International Conference on Machine Learning (Ann Arbor, Michigan, USA,
June12-14, 1988), pages 339-352. Morgan Kaufmann, 1988.
@inproceedings{muggleton/buntine:1988, author = {Stephen H. Muggleton and Wray L. Buntine}, title = {Machine Invention of First-order Predicates by Inverting Resolution}, editor = {John E. Laird}, booktitle = {{ICML'88}: Proceedings of the 5th International Conference on Machine Learning (Ann Arbor, Michigan, USA, June\,12--14, 1988)}, year = 1988, pages = {339--352}, publisher = {Morgan Kaufmann}, isbn = {0-934613-64-8}, keywords = {CIGOL; ilp; inductive programming; ip-system; predicate invention; program synthesis} }
-
Stephen H. Muggleton and Luc De Raedt.
Inductive logic programming: Theory and methods.
Journal of Logic Programming, 19, 20:629-679, May/July
1994.
10th Birthday Special Issue of the Journal of Logic Programming.
@article{muggleton/de-raedt:1994, author = {Muggleton, Stephen H. and De~Raedt, Luc}, title = {Inductive logic programming: {Theory} and methods}, journal = {Journal of Logic Programming}, year = 1994, volume = {19, 20}, pages = {629--679}, month = {May\,/\,July}, note = {10th Birthday Special Issue of the Journal of Logic Programming}, documenturl = {http://www.doc.ic.ac.uk/~shm/Papers/lpj.pdf}, doi = {10.1016/0743-1066(94)90035-3} }
-
Stephen H. Muggleton and C. Feng.
Efficient induction of logic programs.
In ALT'90: Proceedings of the 1st International Conference on
Algorithmic Learning Theory (Tokyo, Japan, Oct.8-10, 1990), pages
368-381. Ohmsha, 1990.
@inproceedings{muggleton/feng:1990, author = {Stephen H. Muggleton and C. Feng}, title = {Efficient Induction of Logic Programs}, booktitle = {{ALT'90}: Proceedings of the 1st {International Conference on Algorithmic Learning Theory} (Tokyo, Japan, Oct.\,8--10, 1990)}, year = 1990, pages = {368--381}, publisher = {Ohmsha}, documenturl = {http://www.doc.ic.ac.uk/~shm/Papers/alt90.pdf}, keywords = {analytical ip; applications; golem; ilp; induction; inductive programming; inproceedings; machine learning; program synthesis}, annote = {golem, efficient rlgg, determinate terms, variable depth} }
-
Stephen H. Muggleton and J. Firth.
CProgol4.4: a tutorial introduction.
In Saso Dzeroski and Nada Lavrac, editors, Relational Data
Mining, pages 160-188. Springer, 2001.
@incollection{muggleton/firth:2001, author = {Stephen H. Muggleton and J. Firth}, title = {{CP}rogol4.4: a tutorial introduction}, editor = {Dzeroski, Saso and Lavrac, Nada}, booktitle = {Relational Data Mining}, publisher = {Springer}, year = 2001, pages = {160--188}, isbn = {978-3-540-42289-1} }
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Stephen H. Muggleton and C. D. Page.
Self-saturation of definite clauses.
In S. Wrobel, editor, ILP'94: Proceedings of the 4th
International Workshop on Inductive Logic Programming (Bonn, Germany,
Sept.12-14, 1994), volume 237 of GMD-Studien, pages 161-174.
Gesellschaft für Mathematik und Datenverarbeitung MBH, 1994.
@inproceedings{muggleton/page:1994, author = {Stephen H. Muggleton and C. D. Page}, title = {Self-saturation of Definite Clauses}, editor = {S. Wrobel}, booktitle = {{ILP'94}: Proceedings of the 4th International Workshop on Inductive Logic Programming (Bonn, Germany, Sept.\,12--14, 1994)}, year = 1994, series = {{GMD}-Studien}, volume = 237, pages = {161--174}, publisher = {{G}esellschaft f{\"{u}}r {M}athematik und {D}atenverarbeitung {MBH}} }
-
Stephen H. Muggleton.
Duce, an oracle-based approach to constructive induction.
In IJCAI'87: Proceedings of the 10th International Joint
Conference on Artificial Intelligence (Milan, Italy, August23-28, 1987),
volume 1, pages 287-292. Morgan Kaufmann, 1987.
@inproceedings{muggleton:1987, author = {Stephen H. Muggleton}, title = {Duce, an Oracle-Based Approach to Constructive Induction}, booktitle = {{IJCAI'87}: Proceedings of the 10th International Joint Conference on Artificial Intelligence (Milan, Italy, August\,23--28, 1987)}, year = 1987, volume = 1, pages = {287--292}, publisher = {Morgan Kaufmann}, keywords = {constructive induction; duce; ilp; inductive programming} }
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Stephen H. Muggleton.
Inductive logic programming.
New Generation Computing, 8(4):295-318, 1991.
@article{muggleton:1991, author = {Stephen H. Muggleton}, title = {Inductive Logic Programming}, journal = {New Generation Computing}, year = 1991, volume = 8, number = 4, pages = {295--318}, annote = {muggleton introduces the term ``inductive logic programming''; he defines ilp as intersection of machine learning and computational logic; seminal paper on ILP}, keywords = {article; ilp; induction; machine learning} }
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Stephen H. Muggleton.
Inductive logic programming: Derivations, successes and shortcomings.
SIGART Bulletin, 5(1):5-11, 1994.
@article{muggleton:1994, author = {Stephen H. Muggleton}, title = {Inductive Logic Programming: Derivations, Successes and Shortcomings}, journal = {SIGART Bulletin}, year = 1994, volume = 5, number = 1, pages = {5--11}, documenturl = {http://www.doc.ic.ac.uk/~shm/Papers/sigart.pdf}, keywords = {article; ilp; induction; machine learning} }
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Stephen H. Muggleton.
Bayesian inductive logic programming.
In COLT'94: Proceedings of the 7th Annual Conference on
Computational Learning Theory (New Brunswick, NJ, USA, July12-15, 1994),
pages 3-11. ACM, 1994.
@inproceedings{muggleton:1994b, author = {Stephen H. Muggleton}, title = {Bayesian Inductive Logic Programming}, booktitle = {{COLT'94}: Proceedings of the 7th Annual Conference on Computational Learning Theory (New Brunswick, NJ, USA, July\,12--15, 1994)}, year = 1994, pages = {3--11}, publisher = {{ACM}}, keywords = {ilp} }
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Stephen H. Muggleton.
Predicate invention and utilization.
Journal of Experimental and Theoretical Artificial
Intelligence, 6(1):121-130, 1994.
@article{muggleton:1994c, author = {Stephen H. Muggleton}, title = {{Predicate invention and utilization}}, journal = {Journal of Experimental and Theoretical Artificial Intelligence}, year = 1994, volume = 6, number = 1, pages = {121--130}, publisher = {Taylor \& Francis}, keywords = {ilp; induction; inductive programming; predicate invention; program synthesis} }
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Stephen H. Muggleton.
Inverse entailment and Progol.
New Generation Computing, 13(3&4):245-286, 1995.
@article{muggleton:1995, author = {Stephen H. Muggleton}, title = {Inverse Entailment and {P}rogol}, journal = {New Generation Computing}, year = 1995, volume = 13, number = {3\,\&\,4}, pages = {245--286}, publisher = {Ohmsha}, documenturl = {http://www.doc.ic.ac.uk/~shm/Papers/InvEnt.ps.gz}, keywords = {ilp; induction; inductive programming; ip-system; learnability; machine learning; progol} }
-
Stephen H. Muggleton.
Inverting implication.
In Machine Intelligence, volume 14. Oxford University Press,
1995.
@incollection{muggleton:1995b, author = {Stephen H. Muggleton}, title = {Inverting implication}, booktitle = {Machine Intelligence}, publisher = {Oxford University Press}, year = 1995, volume = 14 }
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Stephen H. Muggleton.
Learning from positive data.
In Inductive Logic Programming. 6th International Workshop,
ILP-96, Stockholm, Sweden, Aug.26-28, 1996. Selected Papers, volume
1314 of Lecture Notes in Computer Science, pages 358-376,
Berlin/Heidelberg, 1997. Springer.
@inproceedings{muggleton:1997, author = {Stephen H. Muggleton}, title = {Learning from Positive Data}, booktitle = {Inductive Logic Programming. 6th International Workshop, {ILP-96}, Stockholm, Sweden, Aug.\,26--28, 1996. Selected Papers}, year = 1997, series = {Lecture Notes in Computer Science}, volume = 1314, pages = {358--376}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-63494-2}, url = {http://www.springerlink.com/content/q762jww18178v480/}, abstract = {Gold showed in 1967 that not even regular grammars can be exactly identified from positive examples alone. Since it is known that children learn natural grammars almost exclusively from positives examples, Gold's result has been used as a theoretical support for Chomsky's theory of innate human linguistic abilities. In this paper new results are presented which show that within a Bayesian framework not only grammars, but also logic programs are learnable with arbitrarily low expected error from positive examples only. In addition, we show that the upper bound for expected error of a learner which maximises the Bayes' posterior probability when learning from positive examples is within a small additive term of one which does the same from a mixture of positive and negative examples. An Inductive Logic Programming implementation is described which avoids the pitfalls of greedy search by global optimisation of this function during the local construction of individual clauses of the hypothesis. Results of testing this implementation on artificially-generated data-sets are reported. These results are in agreement with the theoretical predictions.}, doi = {10.1007/3-540-63494-0_65}, keywords = {1996; ILP; Muggleton; Progol; inductive logic programming; inproceedings; inverse entailment; } }
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Stephen Muggleton.
Learning the time complexity of logic programs.
In Emanuel Kitzelmann, Roland J. Olsson, and Ute Schmid, editors,
AAIP'05: Proceedings of the 1st Workshop on Approaches and
Applications of Inductive Programming (Bonn, Germany, Aug.7, 2005),
page 9, 2005.
Invited Talk Abstract.
@inproceedings{muggleton:2005, author = {Stephen Muggleton}, title = {Learning the Time Complexity of Logic Programs}, editor = {Emanuel Kitzelmann and Roland J. Olsson and Ute Schmid}, booktitle = {{AAIP'05}: Proceedings of the 1st Workshop on Approaches and Applications of Inductive Programming (Bonn, Germany, Aug.\,7, 2005)}, year = 2005, pages = 9, note = {Invited Talk Abstract}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/aaip05/proceedings/abs_muggleton.pdf} }
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Stephen H. Muggleton, C. H. Bryant, and A. Srinivasan.
Learning Chomsky-like grammars for biological sequence families.
In ICML'00: Proceedings of the 17th International Conference
on Machine Learning (Stanford University, Stanford, CA, USA, June 29-July 2,
2000), pages 631-638. Morgan Kaufmann, 2000.
@inproceedings{muggleton_ea:2000, author = {Stephen H. Muggleton and C. H. Bryant and A. Srinivasan}, title = {Learning {Chomsky}-like Grammars for Biological Sequence Families}, booktitle = {{ICML'00}: Proceedings of the 17th International Conference on Machine Learning (Stanford University, Stanford, CA, USA, June 29--July 2, 2000)}, year = 2000, pages = {631--638}, publisher = {Morgan Kaufmann}, isbn = {1-55860-707-2} }
-
Stephen H. Muggleton, Ramón P. Otero, and Alireza Tamaddoni-Nezhad,
editors.
Inductive Logic Programming. 16th International Conference,
ILP'06, Santiago de Compostela, Spain, Aug.24-27, 2006, Revised Selected
Papers, volume 4455 of Lecture Notes in Computer Science,
Berlin/Heidelberg, 2007. Springer.
@proceedings{muggleton_ea:2007, title = {Inductive Logic Programming. 16th International Conference, {ILP'06}, Santiago de Compostela, Spain, Aug.\,24--27, 2006, Revised Selected Papers}, year = 2007, editor = {Stephen H. Muggleton and Ram{\'o}n P. Otero and Alireza Tamaddoni-Nezhad}, volume = 4455, series = {Lecture Notes in Computer Science}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-73846-6}, url = {http://www.springerlink.com/content/w77q4m266003/}, doi = {10.1007/978-3-540-73847-3} }
-
Claire Nédellec, Céline Rouveirol, Hilde Adé, Francesco Bergadano,
and Birgit Tausend.
Declarative bias in inductive logic programming.
In Luc De Raedt, editor, Advances in Inductive Logic
Programming. IOS Press, 1996.
@incollection{nedellec_ea:1996, author = {Claire N\'{e}dellec and C\'{e}line Rouveirol and Hilde Ad\'{e} and Francesco Bergadano and Birgit Tausend}, title = {Declarative Bias in Inductive Logic Programming}, editor = {De~Raedt, Luc}, booktitle = {Advances in Inductive Logic Programming}, publisher = {IOS Press}, year = 1996, keywords = {bias; declarative bias; ilp; induction; inductive programming; program synthesis} }
-
Jochen Nessel.
Learnability of enumerable classes of recursive functions from
“typical” examples.
In Algorithmic Learning Theory. 10th International Conference,
ALT'99, Tokyo, Japan, Dec.6-8, 1999. Proceedings, volume 1720 of
Lecture Notes in Computer Science, pages 264-275, Berlin/Heidelberg,
2010. Springer.
@inproceedings{nessel:2010, author = {Jochen Nessel}, title = {Learnability of Enumerable Classes of Recursive Functions from ``Typical'' Examples}, booktitle = {Algorithmic Learning Theory. 10th International Conference, {ALT'99}, Tokyo, Japan, Dec.\,6--8, 1999. Proceedings}, year = 2010, series = {Lecture Notes in Computer Science}, volume = 1720, pages = {264--275}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-66748-3}, url = {http://www.springerlink.com/content/r1360773437p3450/}, abstract = {The paper investigates whether it is possible to learn every enumerable classes of recursive functions from typical examples. Typical means, there is a computable family of finite sets, such that for each function in the class there isoneset of examples that can be used inanysuitable hypothesis space for this class of functions. As it will turn out, there are enumerable classes of recursive functions that are not learnable from typical examples. The learnable classes are characterized.}, doi = {10.1007/3-540-46769-6_22} }
-
Shan-Hwei Nienhuys-Cheng and Ronald de Wolf.
Foundations of Inductive Logic Programming, volume 1228 of
Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence.
Springer, 1997.
@book{nienhuys-cheng/wolf:1997, author = {Shan-Hwei Nienhuys-Cheng and Ronald de Wolf}, title = {Foundations of Inductive Logic Programming}, publisher = {Springer}, year = 1997, volume = 1228, series = {Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-62927-6}, url = {http://portal.acm.org/citation.cfm?id=548817}, doi = {10.1007/3-540-62927-0}, keywords = {book; ilp; induction; inductive programming; logic} }
-
Shan-Hwei Nienhuys-Cheng and Roland de Wolf.
Subsumption Theorem and Refutation Completeness, volume 1228 of
Lecture Notes in Computer Science. Lecture Notes in Artificial
Intelligence, chapter 5, pages 75-92.
Springer, Berlin/Heidelberg, 1997.
@inbook{nienhuys-cheng/wolf:1997b, author = {Shan-Hwei Nienhuys-Cheng and Roland de Wolf}, title = {Subsumption Theorem and Refutation Completeness}, chapter = 5, pages = {75--92}, publisher = {Springer}, year = 1997, volume = 1228, series = {Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence}, address = {Berlin\,/\,Heidelberg}, booktitle = {Foundations of Inductive Logic Programming}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-62927-6}, url = {http://www.springerlink.com/content/x244q76778883453/}, doi = {10.1007/3-540-62927-0_5}, keywords = {ilp; logic} }
-
Robert P. Nix.
Editing by example.
ACM Transactions on Programming Languages and Systems,
7(4):600-621, 1985.
@article{nix:1985, author = {Robert P. Nix}, title = {Editing by example}, journal = {{ACM} Transactions on Programming Languages and Systems}, year = 1985, volume = 7, number = 4, pages = {600--621}, address = {New York, NY, USA}, url = {http://doi.acm.org/10.1145/4472.4476}, issn = {0164-0925}, keywords = {1985; Nix; article; editing by example; gap pattern}, publisher = {{ACM}} }
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Roland J. Olsson and D. M. W. Powers.
Machine learning of human language through automatic programming.
In ICCS'03: Proceedings of the 4th International Conference on
Cognitive Science (Sydney, Australia, July13-17, 2003), pages 507-512,
2003.
Together with 7th ASCS Australasian Society for Cognitive Science
Conference.
@inproceedings{olsson/powers:2003, author = {Roland J. Olsson and D. M. W. Powers}, title = {Machine Learning of Human Language through Automatic Programming}, booktitle = {{ICCS'03}: Proceedings of the 4th International Conference on Cognitive Science (Sydney, Australia, July\,13--17, 2003)}, year = 2003, pages = {507--512}, note = {Together with 7th ASCS Australasian Society for Cognitive Science Conference}, documenturl = {http://www-ia.hiof.no/~rolando/200302-ICCS-NLADATE.pdf}, keywords = {adate; enumerative ip; functional programming; ifp; induction; inductive programming; nlp; olsson; program synthesis; program transformation} }
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Ronald J. Olsson and Brock Wilcox.
Self-improvement for the ADATE automatic programming system.
In GECCO'02: Proceedings of the 4th Annual Conference on
Genetic and Evolutionary Computation (New York, USA, July09-13, 2002),
pages 893-897, San Francisco, CA, USA, 2002. Morgan Kaufmann.
@inproceedings{olsson/wilcox:2002, author = {Ronald J. Olsson and Brock Wilcox}, title = {Self-improvement For The {ADATE} Automatic Programming System}, booktitle = {{GECCO'02}: Proceedings of the 4th Annual Conference on Genetic and Evolutionary Computation (New York, USA, July\,09--13, 2002)}, year = 2002, pages = {893--897}, address = {San Francisco, CA, USA}, publisher = {Morgan Kaufmann}, url = {http://portal.acm.org/citation.cfm?id=646205.683108&jmp=cit&coll=GUIDE&dl=GUIDE&CFID=98448670&CFTOKEN=49827412#CIT}, isbn = {1-55860-878-8} }
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Roland J. Olsson.
Inductive functional programming using incremental program
transformation and Execution of logic programs by iterative-deepening A*
SLD-tree search.
Dr scient thesis, University of Oslo, Norway, 1994.
Research report 189.
@phdthesis{olsson:1994, author = {Olsson, Roland J.}, title = {Inductive functional programming using incremental program transformation and Execution of logic programs by iterative-deepening {A}* {SLD}-tree search}, school = {University of Oslo}, year = 1994, type = {Dr scient thesis}, address = {Norway}, note = {Research report 189}, isbn = {82-7368-099-1}, size = {156 pages} }
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Roland J. Olsson.
Inductive functional programming using incremental program
transformation.
Artificial Intelligence, 74(1):55-83, 1995.
@article{olsson:1995, author = {Olsson, Roland J.}, title = {Inductive Functional Programming using Incremental Program Transformation}, journal = {Artificial Intelligence}, year = 1995, volume = 74, number = 1, pages = {55--83}, keywords = {adate; enumerative ip; ifp; induction; inductive programming; program synthesis} }
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Roland J. Olsson.
The art of writing specifications for the ADATEautomatic
programming system.
In John R. Koza, Wolfgang Banzhaf, Kumar Chellapilla, Kalyanmoy Deb,
Marco Dorigo, David B. Fogel, Max H. Garzon, David E. Goldberg, Hitoshi Iba,
and Rick Riolo, editors, GP'98: Proceedings of the Third Annual
Conference (Madison, Wisconsin USA, July22-25, 1998), pages 278-283.
Morgan Kaufmann, 1998.
@inproceedings{olsson:1998, author = {Olsson, Roland J.}, title = {The Art of Writing Specifications for the {ADATE}Automatic Programming System}, editor = {John R. Koza and Wolfgang Banzhaf and Kumar Chellapilla and Kalyanmoy Deb and Marco Dorigo and David B. Fogel and Max H. Garzon and David E. Goldberg and Hitoshi Iba and Rick Riolo}, booktitle = {{GP'98}: Proceedings of the Third Annual Conference (Madison, Wisconsin USA, July\,22--25, 1998)}, year = 1998, pages = {278--283}, publisher = {Morgan Kaufmann}, isbn = {1-55860-548-7}, documenturl = {http://www-ia.hiof.no/~rolando/specart5.ps}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.1763} }
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Roland J. Olsson.
Population management for automatic design of algorithms through
evolution.
In Proceedings of the 1998 IEEE World Congress on
Computational Intelligence, pages 592-597, Anchorage, Alaska, USA, 5-9
1998. IEEE Press.
@inproceedings{olsson:1998b, author = {Olsson, Roland J.}, title = {Population Management for Automatic Design of Algorithms through Evolution}, booktitle = {Proceedings of the 1998 {IEEE} World Congress on Computational Intelligence}, year = 1998, pages = {592--597}, address = {Anchorage, Alaska, USA}, month = {5-9}, publisher = {IEEE Press}, url = {http://citeseer.ist.psu.edu/olsson98population.html} }
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Roland J. Olsson.
How to invent functions.
In Riccardo Poli, Peter Nordin, William B. Langdon, and Terence C.
Fogarty, editors, Genetic Programming. 2nd European Workshop,
EuroGP'99, Göteborg, Sweden, May26-27, 1999. Proceedings, volume 1598
of Lecture Notes in Computer Science, pages 232-243,
Berlin/Heidelberg, 1999. Springer.
@inproceedings{olsson:1999, author = {Olsson, Roland J.}, title = {How to Invent Functions}, editor = {Riccardo Poli and Peter Nordin and William B. Langdon and Terence C. Fogarty}, booktitle = {Genetic Programming. 2nd European Workshop, {EuroGP'99}, G\"oteborg, Sweden, May\,26--27, 1999. Proceedings}, year = 1999, series = {Lecture Notes in Computer Science}, volume = 1598, pages = {232--243}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-65899-3}, url = {http://www.springerlink.com/content/tbvm8wlqcww5tlg7/}, abstract = {The paper presents the abstraction transformation which is a fundamental method for creating functions in ADATE. The use of abstraction turns out to be similar to evolution by gene duplication which is emerging as the most important theory of building blocks in natural genomes. We discuss the relationship between abstraction and its natural counterparts, but also give novel technical details on automatic invention of functions. Basically, abstraction is the reverse of the inlining transformation performed by optimizing compilers.}, doi = {10.1007/3-540-48885-5_20}, documenturl = {http://alife.ccp14.ac.uk/adate/~rolando/abstrart1.ps}, keywords = {adate; enumerative ip; functional programming; ifp; induction; inductive programming; olsson; program synthesis; program transformation} }
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Roland J. Olsson.
Automatic design of algorithms through evolution (ADATE).
In Emanuel Kitzelmann and Ute Schmid, editors, AAIP'07:
Proceedings of the 2nd Workshop on Approaches and Applications of Inductive
Programming (Warsaw, Poland, September17, 2007), page 1, 2007.
Invited Talk.
@inproceedings{olsson:2007, author = {Roland J. Olsson}, title = {Automatic Design of Algorithms through Evolution ({ADATE})}, editor = {Emanuel Kitzelmann and Ute Schmid}, booktitle = {{AAIP'07}: Proceedings of the 2nd Workshop on Approaches and Applications of Inductive Programming (Warsaw, Poland, September\,17, 2007)}, year = 2007, pages = 1, note = {Invited Talk}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/aaip07/aaip_print.pdf}, url = {http://www.cogsys.wiai.uni-bamberg.de/aaip07/} }
-
Bjarte M. Ø stvold.
Inductive synthesis of recursive functional programs (poster
abstract).
In ICFP'97: Proceedings of the 2nd ACM SIGPLAN
international conference on Functional programming (Amsterdam, The
Netherlands, June9-11, 1997), page 323, New York, NY, USA, 1997. ACM.
@inproceedings{ostvold:1997, author = {\O stvold, Bjarte M.}, title = {Inductive synthesis of recursive functional programs (poster abstract)}, booktitle = {{ICFP'97}: Proceedings of the 2nd {ACM} {SIGPLAN} international conference on Functional programming (Amsterdam, The Netherlands, June\,9--11, 1997)}, year = 1997, pages = 323, address = {New York, NY, USA}, publisher = {{ACM}}, url = {http://doi.acm.org/10.1145/258948.258992}, documenturl = {http://portal.acm.org/ft_gateway.cfm?id=258992&type=pdf&coll=GUIDE&dl=GUIDE&CFID=96278412&CFTOKEN=67560760}, isbn = {0-89791-918-1} }
-
Derek Partridge, editor.
Artificial Intelligence and Software Engineering.
Ablex, Norwood, NJ, 1991.
@book{partridge:1991, editor = {Derek Partridge}, title = {Artificial Intelligence and Software Engineering}, publisher = {Ablex}, year = 1991, address = {Norwood, NJ} }
-
Derek Partridge.
The case for inductive programming.
Computer, 30(1):36-41, 1997.
@article{partridge:1997, author = {Derek Partridge}, title = {The Case for Inductive Programming}, journal = {Computer}, year = 1997, volume = 30, number = 1, pages = {36--41}, address = {Los Alamitos, CA, USA}, publisher = {IEEE Computer Society}, keywords = {inductive programming}, url = {http://doi.ieeecomputersociety.org/10.1109/2.562924}, abstract = {The science of creating software is based on deductive methods. But induction, deduction's ignored sibling, could have a profound effect on the future development of computer science theory and practice. Computer scientists and software developers in the late 1960s started a formal science to guide software production. The underlying framework of this science has always been based on deduction (reasoning from the general to the specific) rather than induction (reasoning from the specific to the general). Today inductive programming is found only in "machine learning," a subset of artificial intelligence. Computer scientists may use inductive techniques to explore a philosophy of cognition, develop a theory of adaptive behavior, or find a way around a particularly awkward problem, but they do not use it to create programs. Nearly all basic computing science textbooks fail to include inductive programming. However, inductive reasoning can solve problems outside the realm of machine learning, too. Formal methods to underpin inductive techniques are emerging, but they have yet to be viewed, accepted, and developed as a fundamental alternative to deductive computer science.} }
-
A. Passerini, P. Frasconi, and L. De Raedt.
Kernels on prolog proof trees: Statistical learning in the ilp
setting.
In Emanuel Kitzelmann, Roland J. Olsson, and Ute Schmid, editors,
AAIP'05: Proceedings of the 1st Workshop on Approaches and
Applications of Inductive Programming (Bonn, Germany, Aug.7, 2005), pages
37-48, 2005.
Full Paper.
@inproceedings{passerini_ea:2005, author = {A. Passerini and P. Frasconi and L. De~Raedt}, title = {Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting}, editor = {Emanuel Kitzelmann and Roland J. Olsson and Ute Schmid}, booktitle = {{AAIP'05}: Proceedings of the 1st Workshop on Approaches and Applications of Inductive Programming (Bonn, Germany, Aug.\,7, 2005)}, year = 2005, pages = {37--48}, note = {Full Paper}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/aaip05/proceedings/paper.pdf} }
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Dusko Pavlovic and Douglas R. Smith.
Software development by refinement.
In Formal Methods at the Crossroads: From Panacea to
Foundational Support. 10th Anniversary Colloquium of UNU/IIST the
International Institute for Software Technology of The United Nations
University Lisbon, Portugal, March18-20, 2002. Revised Papers, volume 2757
of Lecture Notes in Computer Science, pages 267-286,
Berlin/Heidelberg, 2003. Springer.
@inproceedings{pavlovic/smith:2003, author = {Pavlovic, Dusko and Smith, Douglas R.}, title = {Software Development by Refinement}, booktitle = { Formal Methods at the Crossroads: From Panacea to Foundational Support. 10th Anniversary Colloquium of {UNU/IIST} the International Institute for Software Technology of The United Nations University Lisbon, Portugal, March\,18-20, 2002. Revised Papers}, year = 2003, series = {Lecture Notes in Computer Science}, volume = 2757, pages = {267--286}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-20527-2}, url = {http://www.springerlink.com/content/tmf8f6tgfyvgdrvp}, doi = {10.1007/978-3-540-40007-3_17}, keywords = {ase; deductive program synthesis; inproceedings; kestrel; overview; program synthesis; software engineering}, abstract = {This paper presents an overview of the technical foundations and current directions of Kestrel’s approach to mechanizing software development. The approach emphasizes machine-supported refinement of property-oriented specifications to code, based on a category of higher-order specifications. A key idea is representing knowledge about programming concepts, such as algorithm design, and datatype refinement by means of taxonomies of design theories and refinements. Concrete refinements are generated by composing library refinements with a specification. The framework is partially implemented in the research systems Specware, Designware, Epoxi, and Planware. Specware provides basic support for composing specifications and refinements via colimit, and for generating code via logic morphisms. Specware is intended to be general-purpose and has found use in industrial settings. Designware extends Specware with taxonomies of software design theories and support for constructing refinements from them. Epoxi builds on Designware to support the specification and refinement of systems. Planware transforms behavioral models of tasks and resources into high-performance scheduling algorithms. A few applications of these systems are presented. ER -} }
-
Nancy Pennington.
Cognitive components of expertise in computer programming: A
review of the literature (Technical report of the Graduate School of
Business, University of Chicago).
University of Chicago, Center for Decision Research, Chicago, 1982.
@book{pennington:1982, author = {Nancy Pennington}, title = {Cognitive components of expertise in computer programming: A review of the literature (Technical report of the Graduate School of Business, University of Chicago)}, publisher = {University of Chicago, Center for Decision Research}, year = 1982, address = {Chicago} }
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P. L. Pirolli and John R. Anderson.
The role of learning from examples in the acquisition of recursive
programming skills.
Canadian Journal of Psychology, 39:240-272, 1985.
@article{pirolli/anderson:1985, author = {P. L. Pirolli and John R. Anderson}, title = {The role of learning from examples in the acquisition of recursive programming skills}, journal = {Canadian Journal of Psychology}, year = 1985, volume = 39, pages = {240--272}, annote = {ute-psylit} }
-
P. L. Pirolli.
A cognitive model and computer tutor for programming recursion.
Human-Computer-Interaction, 2:319-355, 1986.
@article{pirolli:1986, author = {P. L. Pirolli}, title = {A cognitive model and computer tutor for programming recursion}, journal = {Human-Computer-Interaction}, year = 1986, volume = 2, pages = {319--355}, annote = {ute-psylit} }
-
G. D. Plotkin.
A note on inductive generalization.
In B. Meltzer and D. Michie, editors, Machine Intelligence,
volume 5, pages 153-163. Edinburgh University Press, Edinburgh, 1969.
@incollection{plotkin:1969, author = {G. D. Plotkin}, title = {A Note on Inductive Generalization}, editor = {B. Meltzer and D. Michie}, booktitle = {Machine Intelligence}, publisher = {Edinburgh University Press}, year = 1969, volume = 5, pages = {153--163}, address = {Edinburgh} }
-
G. D. Plotkin.
A further note on inductive generalization.
In Machine Intelligence, volume 6, pages 101-124. Edinburgh
University Press, 1971.
@incollection{plotkin:1971, author = {G. D. Plotkin}, title = {A further note on inductive generalization}, booktitle = {Machine Intelligence}, publisher = {Edinburgh University Press}, year = 1971, volume = 6, pages = {101--124}, keywords = {1971; Golem; ILP; Plotkin; inductive logic programming; relative least general generalization; rlgg} }
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G. D. Plotkin.
Automatic Methods of Inductive Inference.
PhD thesis, Edinburgh University, 1971.
@phdthesis{plotkin:1971b, author = {G. D. Plotkin}, title = {Automatic Methods of Inductive Inference}, school = {Edinburgh University}, year = 1971, keywords = {ILP; PhD; Plotkin; inductive logic programming; relative least general generalization; rlgg} }
-
J. Ross Quinlan and R. Mike Cameron-Jones.
FOIL: A midterm report.
In Pavel Brazdil, editor, Machine Learning: ECML-93. European
Conference on Machine Learning, Vienna, Austria, April5-7, 1993.
Proceedings, volume 667 of Lecture Notes in Computer Science, pages
1-20, Berlin/Heidelberg, 1993. Springer.
@inproceedings{quinlan/cameron-jones:1993, author = {J. Ross Quinlan and R. Mike Cameron-Jones}, title = {{FOIL}: {A} Midterm Report}, editor = {Pavel Brazdil}, booktitle = {Machine Learning: {ECML-93}. European Conference on Machine Learning, Vienna, Austria, April\,5--7, 1993. Proceedings}, year = 1993, series = {Lecture Notes in Computer Science}, volume = 667, pages = {1--20}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-56602-1}, url = {http://www.springerlink.com/content/f912432307714257/}, abstract = {FOIL is a learning system that constructs Horn clause programs from examples. This paper summarises the development of FOIL from 1989 up to early 1993 and evaluates its effectiveness on a non-trivial sequence of learning tasks taken from a Prolog programming text. Although many of these tasks are handled reasonably well, the experiment highlights some weaknesses of the current implementation. Areas for further research are identified.}, doi = {10.1007/3-540-56602-3_124}, documenturl = {http://www.rulequest.com/Personal/q+cj.ecml93.ps} }
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J. Ross Quinlan and R. Mike Cameron-Jones.
Induction of logic programs: FOIL and related systems.
New Generation Computing, 13(3&4):287-312, 1995.
@article{quinlan/cameron-jones:1995, author = {J. Ross Quinlan and R. Mike Cameron-Jones}, title = {Induction of Logic Programs: {FOIL} and Related Systems}, journal = {New Generation Computing}, year = 1995, volume = 13, number = {3\&4}, pages = {287--312}, annote = {foil, particularly dealing with closed worlds and making clauses more understandable}, keywords = {FOIL; ILP; inductive logic programming; inductive programming}, url = {http://dblp.uni-trier.de/db/journals/ngc/ngc13.html#QuinlanC95} }
-
J. Ross Quinlan.
Induction of decision trees.
Machine Learning, 1(1):81-106, March 1986.
@article{quinlan:1986, author = {J. Ross Quinlan}, title = {Induction of Decision Trees}, journal = {Machine Learning}, year = 1986, volume = 1, number = 1, pages = {81--106}, month = {March}, publisher = {Springer}, address = {Netherlands}, issn = {0885-6125 (Print) 1573-0565 (Online)}, url = {http://www.springerlink.com/content/q30185t13m5n7000/}, abstract = {The technology for building knowledge-based systems by inductive inference from examples has been demonstrated successfully in several practical applications. This paper summarizes an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail. Results from recent studies show ways in which the methodology can be modified to deal with information that is noisy and/or incomplete. A reported shortcoming of the basic algorithm is discussed and two means of overcoming it are compared. The paper concludes with illustrations of current research directions.}, doi = {10.1023/A:1022643204877}, keywords = {classification; induction; decision trees; information theory; knowledge acquisition; expert systems} }
-
J. Ross Quinlan.
Learning logical definitions from relations.
Machine Learning, 5(3):239-266, August 1990.
Original foil paper.
@article{quinlan:1990, author = {J. Ross Quinlan}, title = {Learning Logical Definitions from Relations}, journal = {Machine Learning}, year = 1990, volume = 5, number = 3, pages = {239--266}, month = {August}, note = {Original foil paper}, publisher = {Springer}, address = {Netherlands}, issn = {0885-6125 (Print) 1573-0565 (Online)}, url = {http://www.springerlink.com/content/r7155207778n7730/}, abstract = {This paper describes FOIL, a system that learns Horn clauses from data expressed as relations. FOIL is based on ideas that have proved effective in attribute-value learning systems, but extends them to a first-order formalism. This new system has been applied successfully to several tasks taken from the machine learning literature.}, doi = {10.1023/A:1022699322624}, keywords = {FOIL; ILP; Induction; empirical learning; first order rules; inductive logic programming; inductive programming; relational data; } }
-
J. Ross Quinlan.
Determinate literals in inductive logic programming.
In John Mylopoulos and Raymond Reiter, editors, IJCAI'91:
Proceedings of the 12th International Joint Conference on Artificial
Intelligence (Sydney, Australia, Aug.24-30, 1991). Morgan Kaufmann, 1991.
@inproceedings{quinlan:1991, author = {J. Ross Quinlan}, title = {Determinate Literals in Inductive Logic Programming}, editor = {Mylopoulos, John and Reiter, Raymond}, booktitle = {{IJCAI}'91: Proceedings of the 12th International Joint Conference on Artificial Intelligence (Sydney, Australia, Aug.\,24--30, 1991)}, year = 1991, publisher = {Morgan Kaufmann}, isbn = {1-55860-160-0}, documenturl = {http://dli.iiit.ac.in/ijcai/IJCAI-91-VOL2/PDF/021.pdf}, keywords = {applications; enumerative ip; foil; ilp; induction; inductive programming; inproceedings; machine learning; program synthesis}, abstract = {A recent system, FOIL, constructs Horn programs from numerous examples. Computational efficiency is achieved by using greedy search guided by an information-based heuristic. Greedy search tends to be myopic but determinate terms, an adaptation of an idea introduced by another new system (GOLEM), has been found to provide many of the benefits of lookahead without substantial increases in computation. This paper sketches key ideas from FOIL and GOLEM and discusses the use of determinate literals in a greedy search context. The efficacy of this approach is illustrated on the task of learning the quicksort procedure and other small but non-trivial list-manipulation functions. } }
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J. Ross Quinlan.
Boosting first-order learning.
In Setsuo Arikawa and Arun Sharma, editors, Algorithmic Learning
Theory. 7th International Workshop, ALT'96, Sydney, Australia,
Oct.23-25, 1996. Proceedings, volume 1160 of Lecture Notes in
Computer Science, pages 143-155, Berlin/Heidelberg, 1996. Springer.
@inproceedings{quinlan:1996, author = {J. Ross Quinlan}, title = {Boosting First-Order Learning}, editor = {Setsuo Arikawa and Arun Sharma}, booktitle = {Algorithmic Learning Theory. 7th International Workshop, {ALT'96}, Sydney, Australia, Oct.\,23--25, 1996. Proceedings}, year = 1996, series = {Lecture Notes in Computer Science}, volume = 1160, pages = {143--155}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, keywords = {1996; Boosting; FFOIL; ILP; Quinlan; inductive logic programming; }, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-61863-8}, url = {http://www.springerlink.com/content/yw27157006846372/}, abstract = {Several empirical studies have confirmed that boosting classifier-learning systems can lead to substantial improvements in predictive accuracy. This paper reports early experimental results from applying boosting toffoil, a first-order system that constructs definitions of functional relations. Although the evidence is less convincing than that for propositional-level learning systems, it suggests that boosting will also prove beneficial for first-order induction.}, doi = {10.1007/3-540-61863-5_42} }
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J. Ross Quinlan.
Learning first-order definitions of functions.
Journal of Artificial Intelligence Research, 5:139-161, 1996.
@article{quinlan:1996b, author = {J. Ross Quinlan}, title = {Learning First-Order Definitions of Functions}, journal = {Journal of Artificial Intelligence Research}, year = 1996, volume = 5, pages = {139--161}, editor = {Steven Minton}, keywords = {applications; article; enumerative ip; foil; ilp; induction; inductive programming; machine learning; program synthesis}, annote = {ffoil, tackles some problems of foil when learning functional relations}, abstract = {First-order learning involves finding a clause-form definition of a relation from examples of the relation and relevant background information. In this paper, a particular first-order learning system is modified to customize it for finding definitions of functional relations. This restriction leads to faster learning times and, in some cases, to definitions that have higher predictive accuracy. Other first-order learning systems might benefit from similar specialization.}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.47.5035}, documenturl = {http://www.jair.org/media/308/live-308-1570-jair.pdf} }
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J. Ross Quinlan.
Relational learning and boosting.
In Saso Dzeroski and Nada Lavrac, editors, Relational Data
Mining, chapter 12, pages 292-304. Springer, New York, NY, USA, 2001.
@incollection{quinlan:2001, author = {J. Ross Quinlan}, title = {Relational learning and boosting}, editor = {Saso Dzeroski and Nada Lavrac}, booktitle = {Relational Data Mining}, publisher = {Springer}, year = 2001, chapter = 12, pages = {292--304}, address = {New York, NY, USA}, abstract = {Boosting, a methodology for constructing and combining multiple classifiers, has been found to lead to substantial improvements in predictive accuracy. Although boosting was formulated in a propositional learning context, the same ideas can be applied to first-order learning (also known as inductive logic programming). Boosting is used here with a system that learns relational definitions of functions. Results show that the occasional negative impact of boosting all resemble the corresponding observations for propositional learning.}, isbn = {3-540-42289-7}, keywords = {FFOIL; FOIL; ILP; boosting; inductive logic programming; inductive programming}, url = {http://portal.acm.org/citation.cfm?id=567237#} }
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M. R. K. Krishna Rao.
A class of Prolog programs inferable from positive data.
In S. Arikawa and A. K. Sharma, editors, Algorithmic Learning
Theory. 7th International Workshop, ALT'96, Sydney, Australia,
Oct.23-25, 1996. Proceedings, volume 1160 of Lecture Notes in
Computer Science, pages 272-284, Berlin/Heidelberg, 1996. Springer.
@inproceedings{rao:1996, author = {M. R. K. Krishna Rao}, title = {A class of {Prolog} programs inferable from positive data}, editor = {S. Arikawa and A. K. Sharma}, booktitle = {Algorithmic Learning Theory. 7th International Workshop, {ALT'96}, Sydney, Australia, Oct.\,23--25, 1996. Proceedings}, year = 1996, series = {Lecture Notes in Computer Science}, volume = 1160, pages = {272--284}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-61863-8}, url = {http://www.springerlink.com/content/p375410783158155/}, abstract = {In this paper, we identify a class of Prolog programs inferable from positive data. Our approach is based on moding information and linear predicate inequalities between input terms and output terms. Our results generalize the results of Arimura and Shinohara [4]. Standard programs for reverse, quick-sort, merge-sort are a few examples of programs that can be handled by our results but not by the earlier results of [4]. The generality of our results follows from the fact that we treat logical variables as transmitters for broadcasting communication, whereas Arimura and Shinohara [4] treat them as point-to-point communication channels.}, doi = {10.1007/3-540-61863-5_52}, annote = {ute-inflit} }
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M. R. K. Krishna Rao.
A framework for incremental learning of logic programs.
Theoretical Computer Science, 185(1):191-213, 1997.
@article{rao:1997, author = {M. R. K. Krishna Rao}, title = {A framework for incremental learning of logic programs}, journal = {Theoretical Computer Science}, year = 1997, volume = 185, number = 1, pages = {191--213}, publisher = {Elsevier Science Publishers Ltd.}, address = {Essex, UK}, url = {http://dx.doi.org/10.1016/S0304-3975(97)00021-2} }
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M. R. K. Krishna Rao.
Some classes of prolog programs inferable from positive data.
Theoretical Computer Science, 241(1-2):211-234, 2000.
Special issue for ALT'96.
@article{rao:2000, author = {M. R. K. Krishna Rao}, title = {Some classes of Prolog programs inferable from positive data}, journal = {Theoretical Computer Science}, year = 2000, volume = 241, number = {1-2}, pages = {211--234}, note = {Special issue for {ALT'96}} }
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M. R. K. Krishna Rao.
Inductive inference of term rewriting systems from positive data.
In Algorithmic Learning Theory. 15th International Conference,
ALT'04, Padova, Italy, Oct.2-5, 2004. Proceedings, volume 3244 of
Lecture Notes in Artificial Intelligence, pages 69-82,
Berlin/Heidelberg, 2004. Springer.
@inproceedings{rao:2004, author = {M. R. K. Krishna Rao}, title = {Inductive Inference of Term Rewriting Systems from Positive Data}, booktitle = {Algorithmic Learning Theory. 15th International Conference, {ALT'04}, Padova, Italy, Oct.\,2--5, 2004. Proceedings}, year = 2004, series = {Lecture Notes in Artificial Intelligence}, volume = 3244, pages = {69--82}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, url = {http://www.springerlink.com/content/da9c44u3ueljj227}, doi = {10.1007/978-3-540-30215-5_7}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-23356-5}, keywords = {inductive programming; learnability; program synthesis; term rewriting}, abstract = {In this paper, we study inferability of term rewriting systems from positive examples alone. We define a class of simple flat term rewriting systems that are inferable from positive examples. In flat term rewriting systems, nesting of defined symbols is forbidden in both left- and right-hand sides. A flat TRS is simple if the size of redexes in the right-hand sides is bounded by the size of the corresponding left-hand sides. The class of simple flat TRSs is rich enough to include many divide-and-conquer programs like addition, doubling, tree-count, list-count, split, append, etc. The relation between our results and the known results on Prolog programs is also discussed. In particular, flat TRSs can define functions (like doubling), whose output is bigger in size than the input, which is not possible with linearly-moded Prolog programs.} }
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M. R. K. Krishna Rao.
A class of prolog programs with non-linear outputs inferable from
positive data.
In Algorithmic Learning Theory. 16th International Conference,
ALT 2005, Singapore, October 8-11, 2005. Proceedings, volume 3734 of
Lecture Notes in Computer Science, pages 312-326, Berlin/Heidelberg,
2005. Springer.
@inproceedings{rao:2005, author = {M. R. K. Krishna Rao}, title = {A Class of Prolog Programs with Non-linear Outputs Inferable from Positive Data}, booktitle = {Algorithmic Learning Theory. 16th International Conference, ALT 2005, Singapore, October 8-11, 2005. Proceedings}, year = 2005, series = {Lecture Notes in Computer Science}, volume = 3734, pages = {312--326}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-29242-5}, url = {http://www.springerlink.com/content/aav9qlrv8df5j3g1/}, abstract = {In this paper, we study inferability of Prolog programs from positive examples alone. We define a class of Prolog programs called recursion bounded programs that can capture non-linear relationships between inputs and outputs and yet inferable from positive examples. This class is rich enough to include many programs like append, delete, insert, reverse, permute, count, listsum, listproduct, insertion-sort, quick-sort on lists, various tree traversal programs and addition, multiplication, factorial, power on natural numbers. The relation between our results and the known results is also discussed. In particular, the class of recursion bounded programs contains all the known terminating linearly-moded Prolog programs of Krishna Rao [7] and additional programs like power on natural numbers which do not belong to the class of linearly-moded programs and the class of safe programs of Martin and Sharma [12].}, doi = {10.1007/11564089_25} }
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M. R. K. Krishna Rao.
Learnability of simply-moded logic programs from entailment.
In Advances in Computer Science - ASIAN'04. Higher-Level
Decision Making. 9th Asian Computing Science Conference. Dedicated to
Jean-Louis Lassez on the Occasion of His 60th Birthday. Chiang Mai, Thailand,
Dec.8-10, 2004. Proceedings, volume 3321 of Lecture Notes in
Computer Science, pages 128-141, Berlin/Heidelberg, 2005. Springer.
@inproceedings{rao:2005b, author = {M. R. K. Krishna Rao}, title = {Learnability of Simply-Moded Logic Programs from Entailment}, booktitle = {Advances in Computer Science -- {ASIAN'04}. Higher-Level Decision Making. 9th Asian Computing Science Conference. Dedicated to Jean-Louis Lassez on the Occasion of His 60th Birthday. Chiang Mai, Thailand, Dec.\,8--10, 2004. Proceedings}, year = 2005, series = {Lecture Notes in Computer Science}, volume = 3321, pages = {128--141}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, url = {http://www.springerlink.com/content/ckanleyfx7ahm740}, keywords = {ilp; inductive programming; learnability; program synthesis; recursion}, abstract = {In this paper, we study exact learning of logic programs from entailment queries and present a polynomial time algorithm to learn a rich class of logic programs that allow local variables and include many standard programs like addition, multiplication, exponentiation, member, prefix, suffix, length, append, merge, split, delete, insert, insertion-sort, quick-sort, merge-sort, preorder and inorder traversal of binary trees, polynomial recognition, derivatives, sum of a list of naturals. Our algorithm asks at most polynomial number of queries and our class is the largest of all the known classes of programs learnable from entailment.}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-24087-7}, doi = {10.1007/978-3-540-30502-6_9} }
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M. R. K. Krishna Rao.
Learning recursive prolog programs with local variables from
examples.
In Emanuel Kitzelmann, Roland J. Olsson, and Ute Schmid, editors,
AAIP'05: Proceedings of the 1st Workshop on Approaches and
Applications of Inductive Programming (Bonn, Germany, Aug.7, 2005), pages
51-57, 2005.
Full Paper.
@inproceedings{rao:2005c, author = {M. R. K. Krishna Rao}, title = {Learning Recursive Prolog Programs with Local Variables from Examples}, editor = {Emanuel Kitzelmann and Roland J. Olsson and Ute Schmid}, booktitle = {{AAIP'05}: Proceedings of the 1st Workshop on Approaches and Applications of Inductive Programming (Bonn, Germany, Aug.\,7, 2005)}, year = 2005, pages = {51--57}, note = {Full Paper}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/aaip05/proceedings/aaip_krishna.pdf} }
-
M. R. K. Krishna Rao.
Learnability of term rewrite systems from positive examples.
In CATS'06: Proceedings of the 12th Computing: The
Australasian Theroy Symposium (Hobart, Australia, Jan.16-19, 2006),
volume 51, pages 133-137. Australian Computer Society, Inc., 2006.
@inproceedings{rao:2006, author = {M. R. K. Krishna Rao}, title = {Learnability of Term Rewrite Systems from Positive Examples}, booktitle = {{CATS'06}: Proceedings of the 12th Computing: The Australasian Theroy Symposium (Hobart, Australia, Jan.\,16--19, 2006)}, year = 2006, volume = 51, pages = {133--137}, publisher = {Australian Computer Society, Inc.}, url = {http://portal.acm.org/citation.cfm?id=1151801}, keywords = {inductive programming; learnability; program synthesis; term rewriting}, abstract = {Learning from examples is an important characteristic feature of intelligence in both natural and artificial intelligent agents. In this paper, we study learnability of term rewriting systems from positive examples alone. We define a class of linear-bounded term rewriting systems that are inferable from positive examples. In linear-bounded term rewriting systems, nesting of defined symbols is allowed in right-hand sides, unlike the class of flat systems considered in Krishna Rao [8]. The class of linear-bounded TRSs is rich enough to include many divide-and-conquer programs like addition, logarithm, tree-count, list-count, split, append, reverse etc.} }
-
M. R. K. Krishna Rao.
Some classes of term rewriting systems inferable from positive data.
Theoretical Computer Science, 397(1-3):129-149, 2008.
@article{rao:2008, author = {M. R. K. Krishna Rao}, title = {Some Classes of Term Rewriting Systems Inferable from Positive Data}, journal = {Theoretical Computer Science}, year = 2008, volume = 397, number = {1-3}, pages = {129--149}, address = {Essex, UK}, publisher = {Elsevier Science Publishers Ltd.}, url = {http://dx.doi.org/10.1016/j.tcs.2008.02.027}, keywords = {inductive programming; learnability; program synthesis; term rewriting}, abstract = {In this paper, we study the inferability of term rewriting systems (trss, for short) from positive examples alone. Two classes of trss inferable from positive data are presented, namely, simple flat trss and linear-bounded trss. These classes of trss are rich enough to include many divide-and-conquer programs like addition, doubling, logarithm, tree-count, list-count, split, append, reverse, etc. The classes of simple flat trss and linear-bounded trss are incomparable, i.e., there are functions that can be computed by simple flat trss but not by linear-bounded trss and vice versa.} }
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J. C. Reynolds.
Towards a theory of type structure.
In Programming Symposium. Proceedings, Colloque sur la
Programmation Paris, April9-11, 1974, volume 19 of Lecture Notes in
Computer Science, pages 408-425, Berlin/Heidelberg, 1974. Springer.
@inproceedings{reynolds:1974, author = {J. C. Reynolds}, title = {Towards a Theory of Type Structure}, booktitle = {Programming Symposium. Proceedings, Colloque sur la Programmation Paris, April\,9--11, 1974}, year = 1974, series = {Lecture Notes in Computer Science}, volume = 19, pages = {408--425}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-06859-4}, url = {http://www.springerlink.com/content/p5801737k78207p7/}, abstract = {Without Abstract}, doi = {10.1007/3-540-06859-7_148}, keywords = {lambda calculus; recursion theory; seminal paper; system f}, annote = {one of the two original works on system f} }
-
C. Rich and Richard C. Waters.
The programmer's apprentice: a session with KBEmacs.
Number 11 in IEEE Transactions on Software Engineering. IEEE Press,
November 1985.
@book{rich/waters:1985, author = {C. Rich and Richard C. Waters}, title = {The programmer's apprentice: a session with {KBE}macs}, publisher = {IEEE Press}, year = 1985, series = {IEEE Transactions on Software Engineering}, month = {November}, pages = {1296--1320}, number = 11, abstract = {The Knowledge-Based Editor in Emacs (KBEmacs) is the current demonstration system implemented as part of the Programmer's Apprentice project. KBEmacs is capable of acting as a semiexpert assistant to a person who is writing a program-taking over some parts of the programming task. Using KBEmacs, it is possible to construct a program by issuing a series of high level comnmands. This series of commands can be as much as an order of magnitude shorter than the program it describes.}, doi = {http://doi.ieeecomputersociety.org/10.1109/TSE.1985.231880}, keywords = {Programmer's Apprentice; Computer-aided design; program editing; programming environments; reusable software components} }
-
C. Rich and Richard C. Waters.
Automatic programming: Myths and prospects.
IEEE Computer, 21(11):10-25, 1988.
@article{rich/waters:1988, author = {C. Rich and Richard C. Waters}, title = {Automatic programming: {Myths} and prospects}, journal = {IEEE Computer}, year = 1988, volume = 21, number = 11, pages = {10--25} }
-
Charles Rich and Richard C. Waters.
Approaches to automatic programming.
In M. C. Yovits, editor, Advances in Computers, volume 37.
Academic Press, 1993.
@incollection{rich/waters:1993, author = {Charles Rich and Richard C. Waters}, title = {Approaches to Automatic Programming}, editor = {M. C. Yovits}, booktitle = {Advances in Computers}, publisher = {Academic Press}, year = 1993, volume = 37 }
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Riverson Rios and Stan Matwin.
Efficient induction of recursive prolog definitions.
In Advances in Artifical Intelligence. 11th Biennial Conference
of the Canadian Society for Computational Studies of Intelligence, AI'96
Toronto, Ontario, Canada, May21-24, 1996. Proceedings, volume 1081 of
Lecture Notes in Computer Science, pages 240-248,
Berlin/Heidelberg, 1996. Springer.
@inproceedings{rios/matwin:1996, author = {Riverson Rios and Stan Matwin}, title = {Efficient Induction of Recursive Prolog Definitions}, booktitle = {Advances in Artifical Intelligence. 11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, {AI'96} Toronto, Ontario, Canada, May\,21--24, 1996. Proceedings}, year = 1996, series = {Lecture Notes in Computer Science}, volume = 1081, pages = {240--248}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-61291-9}, url = {http://www.springerlink.com/content/78q08572p5m82450/}, doi = {10.1007/3-540-61291-2_55}, keywords = {CLAM; ilp; inductive programming; ip-system; program synthesis; recursion}, abstract = {The ability to learn recursive definitions is a desirable characteristic of a learner. This paper presents Clam, a system that efficiently learns Prolog purely and left-recursive definitions from small data sets by using inverse implication. A learning curve for Clam shows that the accuracy grows with the increase of both positive and negative examples. We believe our system can be used as a preprocessor for a general-purpose system when few examples are at hand.} }
-
E. S. Roberts.
Thinking recursively.
Wiley, New York, 1986.
@book{roberts:1986, author = {E. S. Roberts}, title = {Thinking recursively}, publisher = {Wiley}, year = 1986, address = {New York} }
-
Raúl Rojas.
Neural Networks - A Systematic Introduction.
Springer, 1996.
@book{rojas:1996, author = {Ra\'{u}l Rojas}, title = {Neural Networks -- A Systematic Introduction}, publisher = {Springer}, year = 1996, keywords = {neuralnetworks} }
-
Paul S. Rosenbloom and Alan Newell.
The chunking of goal hierarchies: A generalized model of practice.
In Ryszard S. Michalski, Jaime G. Carbonell, and Tom M. Mitchell,
editors, Machine Learning. An Artificial Intelligence Approach,
volume 2, chapter 10, pages 247-288. Morgan Kaufmann, Los Altos, CA, 1986.
@incollection{rosenbloom/newell:1986, author = {Paul S. Rosenbloom and Alan Newell}, title = {The Chunking of Goal Hierarchies: A Generalized Model of Practice}, editor = {Ryszard S. Michalski and Jaime G. Carbonell and Tom M. Mitchell}, booktitle = {Machine Learning. An Artificial Intelligence Approach}, publisher = {Morgan Kaufmann}, year = 1986, volume = 2, chapter = 10, pages = {247--288}, address = {Los Altos, CA}, keywords = {cognition} }
-
Stuart Russell and Peter Norvig.
Artificial Intelligence: A Modern Approach.
Prentice Hall, 3 edition, 2010.
@book{russell/norvig:2010, author = {Stuart Russell and Peter Norvig}, title = {Artificial Intelligence: A Modern Approach}, publisher = {Prentice Hall}, year = 2010, edition = 3, keywords = {ai} }
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Ken Sadohara and Makoto Haraguchi.
Analogical logic program synthesis from examples.
In Nada Lavrac and Stefan Wrobel, editors, Machine Learning:
ECML-95. 8th European Conference on Machine Learning Heraclion, Crete,
Greece, April25-27, 1995. Proceedings, volume 912 of Lecture Notes
in Computer Science. Lecture Notes in Artificial Intelligence, pages
232-244, Berlin/Heidelberg, 1995. Springer.
@inproceedings{sadohara/haraguchi:1995, author = {Ken Sadohara and Makoto Haraguchi}, title = {Analogical logic program synthesis from examples}, editor = {Nada Lavrac and Stefan Wrobel}, booktitle = {Machine Learning: {ECML-95}. 8th European Conference on Machine Learning Heraclion, Crete, Greece, April\,25--27, 1995. Proceedings}, year = 1995, series = {Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence}, volume = 912, pages = {232--244}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-59286-0}, url = {http://www.springerlink.com/content/7881314375u15320/}, abstract = {The purpose of this paper is to present a theory and an algorithm for analogical logic program synthesis from examples. Given a source program and examples, the task of our algorithm is to find a program which explains the examples correctly and is similar to the source program. Although we can define a notion of similarity in various ways, we consider a class of similarities from the viewpoint of how examples are explained by a program. In a word, two programs are said to be similar if they share a common explanation structure at an abstract level. Using this notion of similarity, we formalize an analogical logic program synthesis and show that our algorithm based on a framework of model inference can identify a desired program.}, doi = {10.1007/3-540-59286-5_61}, annote = {ute-inflit} }
-
Yasubumi Sakakibara.
Learning context-free grammars from structural data in polynomial
time.
Theoretical Computer Science, 76(2-3):223-242, November 1990.
@article{sakakibara:1990, author = {Yasubumi Sakakibara}, title = {Learning Context-free Grammars from Structural Data in Polynomial Time}, journal = {Theoretical Computer Science}, year = 1990, volume = 76, number = {2--3}, pages = {223--242}, month = {November}, publisher = {Elsevier Science Publishers Ltd.}, address = {Essex, UK}, doi = {10.1016/0304-3975(90)90017-C}, annote = {ute-inflit} }
-
Yasubumi Sakakibara.
Efficient learning of context-free grammars from positive structural
examples.
Information and Computation, 97:23-60, 1992.
@article{sakakibara:1992, author = {Yasubumi Sakakibara}, title = {Efficient Learning of Context-Free Grammars from Positive Structural Examples}, journal = {Information and Computation}, year = 1992, volume = 97, pages = {23--60}, annote = {ute-inflit} }
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Yasubumi Sakakibara.
Recent advances of grammatical inference.
Theoretical Computer Science, 185(1):15-45, October 1997.
@article{sakakibara:1997, author = {Yasubumi Sakakibara}, title = {Recent Advances of Grammatical Inference}, journal = {Theoretical Computer Science}, year = 1997, volume = 185, number = 1, pages = {15--45}, month = {October}, publisher = {Elsevier Science Publishers Ltd.}, address = {Essex, UK}, doi = {10.1016/S0304-3975(97)00014-5}, annote = {ute-inflit} }
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K. Schädler, U. Schmid, B. Machenschalk, and H. Lübben.
A neural net for determining structural similarity of recursive
programs.
In R. Bergmann and W. Wilke, editors, GWCBR'97: Proceedings of
the 5th German Workshop on Case-Based Reasoning. Foundations, Systems, and
Applications (Bad Honnef, Germany, March4-5, 1997), pages 199-206, 1997.
LSA-97-01E.
@inproceedings{schaedler_ea:1997, author = {Sch{\"a}dler, K. and Schmid, U. and Machenschalk, B. and L{\"u}bben, H.}, title = {A neural net for determining structural similarity of recursive programs}, editor = {Bergmann, R. and Wilke, W.}, booktitle = {{GWCBR'97}: Proceedings of the 5th German Workshop on Case-Based Reasoning. Foundations, Systems, and Applications (Bad Honnef, Germany, March\,4--5, 1997)}, year = 1997, pages = {199--206}, note = {LSA-97-01E} }
-
Ute Schmid and Roland J. Olsson, editors.
Special Topic on Approaches and Applications of Inductive
Programming, volume 7.
MIT Press, 2006.
@book{schmid/olsson:2006, editor = {Ute Schmid and Roland J. Olsson}, title = {Special Topic on Approaches and Applications of Inductive Programming}, publisher = {MIT Press}, year = 2006, volume = 7, journal = {Journal of Machine Learning Research}, url = {http://jmlr.csail.mit.edu/papers/topic/inductive_programming.html} }
-
Ute Schmid and Jens Waltermann.
Automatic synthesis of XSL-transformations from example documents.
In M. H. Hamza, editor, AIA'04: Proceedings of the IASTED
International Conference on Artificial Intelligence and Applications
Proceedings (Innsbruck, Austria, Febr.16-18, 2004), Artificial
Intelligence and Soft Computing, pages 252-257, Anaheim, 2004. Acta Press.
@inproceedings{schmid/waltermann:2004, author = {Ute Schmid and Jens Waltermann}, title = {Automatic Synthesis of {XSL}-Transformations from Example Documents}, editor = {Hamza, M. H.}, booktitle = {{AIA'04}: Proceedings of the {IASTED} International Conference on Artificial Intelligence and Applications Proceedings (Innsbruck, Austria, Febr.\,16--18, 2004)}, year = 2004, series = {Artificial Intelligence and Soft Computing}, pages = {252--257}, address = {Anaheim}, publisher = {Acta Press} }
-
Ute Schmid and Fritz Wysotzki.
Induction of recursive program schemes.
In Claire Nedellec and Céline Rouveirol, editors, Machine
Learning: ECML-98. 10th European Conference on Machine Learning, Chemnitz,
Germany, April21-23, 1998. Proceedings, volume 1398 of Lecture Notes
in Computer Science, pages 214-225, Berlin/Heidelberg, 1998. Springer.
@inproceedings{schmid/wysotzki:1998, author = {Schmid, Ute and Wysotzki, Fritz}, title = {Induction of Recursive Program Schemes}, editor = {Claire Nedellec and C{\'e}line Rouveirol}, booktitle = {Machine Learning: {ECML-98}. 10th European Conference on Machine Learning, Chemnitz, Germany, April\,21--23, 1998. Proceedings}, year = 1998, series = {Lecture Notes in Computer Science}, volume = 1398, pages = {214--225}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-64417-0}, url = {http://www.springerlink.com/content/w607kk31573q1835/}, abstract = {In this paper we present an approach to the induction of recursive structures from examples which is based on the notion of recursive program schemes. We separate induction from examples in two stages: (1) constructing initial programs from examples and (2) folding initial programs to recursive program schemes. By this separation, the induction of recursive program schemes can be reduced to a pattern-matching problem which can be handled by a generic algorithm. Construction of initial programs is performed with an approach to universal planning.Background knowledgeBackground knowledgeis given in the form of operators and their conditions of application. Furthermore synthesizing recursive program schemes instead of programs in a predefined programming language enables us to combine program synthesis and analogical reasoning. A recursive program scheme represents the class of structural identical programs and can be assigned different semantics by interpretation. We believe that our approach mimicks in some way the problem solving and learning behavior of a (novice) human programmer and that our approach integrates theoretical ideas and empirical results of learning by doing and learning by analogy from cognitive science in a unique framework.is given in the form of operators and their conditions of application. Furthermore synthesizing recursive program schemes instead of programs in a predefined programming language enables us to combine program synthesis and analogical reasoning. A recursive program scheme represents the class of structural identical programs and can be assigned different semantics by interpretation. We believe that our approach mimicks in some way the problem solving and learning behavior of a (novice) human programmer and that our approach integrates theoretical ideas and empirical results of learning by doing and learning by analogy from cognitive science in a unique framework.}, keywords = {Inductive Program Synthesis; Planning and Learning; Analogy; Cognitive Modelling}, doi = {10.1007/BFb0026692} }
-
Ute Schmid and Fritz Wysotzki.
Skill acquisition can be regarded as program synthesis: An
integrative approach to learning by doing and learning by analogy.
In J. Krems, Ute Schmid, and Fritz Wysotzki, editors, Mind
Modelling. A Cognitive Science Approach to Reasoning, Learning and
Discovery, pages 253-284. Pabst Science Publishers, Lengerich, 1999.
@incollection{schmid/wysotzki:1999, author = {Ute Schmid and Fritz Wysotzki}, title = {Skill acquisition can be regarded as program synthesis: An integrative approach to learning by doing and learning by analogy}, editor = {J. Krems and Ute Schmid and Fritz Wysotzki}, booktitle = {Mind Modelling. A Cognitive Science Approach to Reasoning, Learning and Discovery}, publisher = {Pabst Science Publishers}, year = 1999, pages = {253--284}, address = {Lengerich}, url = {http://www.pabst-publishers.de/Psychologie/Buecher/buch99.htm} }
-
Ute Schmid and Fritz Wysotzki.
Applying inductive program synthesis to macro learning.
In Steve Chien, Subbarao Kambhampati, and Craig A. Knoblock, editors,
AIPS'00: Proceedings of the Fifth International Conference on
Artificial Intelligence Planning Systems (Breckenridge, CO, USA,
April14-17, 2000), pages 371-378, Menlo Park, CA, 2000. AAAI Press.
@inproceedings{schmid/wysotzki:2000, author = {Ute Schmid and Fritz Wysotzki}, title = {Applying Inductive Program Synthesis to Macro Learning}, editor = {Steve Chien and Subbarao Kambhampati and Craig A. Knoblock}, booktitle = {{AIPS'00}: Proceedings of the Fifth International Conference on Artificial Intelligence Planning Systems (Breckenridge, CO, USA, April\,14--17, 2000)}, year = 2000, pages = {371--378}, address = {Menlo Park, CA}, publisher = {AAAI Press}, isbn = {1-57735-111-8}, keywords = {inductive programming; planning} }
-
Ute Schmid and Fritz Wysotzki.
A unifying approach to learning by doing and learning by analogy.
In N. Callaos, editor, SCI'00: 4th World Multiconference on
Systemics, Cybernetics and Informatics (Orlando, Florida, July23-26,
2000), volume 1, pages 379-384, Orlando, FL, 2000. International Institute
of Informatics and Systemics.
@inproceedings{schmid/wysotzki:2000b, author = {Ute Schmid and Fritz Wysotzki}, title = {A Unifying Approach to Learning by Doing and Learning by Analogy}, editor = {N. Callaos}, booktitle = {{SCI'00}: 4th World Multiconference on Systemics, Cybernetics and Informatics (Orlando, Florida, July\,23--26, 2000)}, year = 2000, volume = 1, pages = {379--384}, address = {Orlando, FL}, publisher = {International Institute of Informatics and Systemics}, isbn = {980-07-6687-1} }
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Ute Schmid and Fritz Wysotzki.
Applying Inductive Program Synthesis to Learning Domain-Dependent
Control Knowledge - Transforming Plans into Programs.
Technical Report CMU-CS-00-143, Computer Science Department, Carnegie
Mellon University, Pittsburg, PA, 2000.
@techreport{schmid/wysotzki:2000c, author = {Ute Schmid and Fritz Wysotzki}, title = {{Applying Inductive Program Synthesis to Learning Domain-Dependent Control Knowledge -- Transforming Plans into Programs}}, institution = {Computer Science Department, Carnegie Mellon University}, year = 2000, number = {CMU-CS-00-143}, address = {Pittsburg, PA} }
-
Ute Schmid and Fritz Wysotzki.
Applying inductive programm synthesis to macro learning.
In Steve Chien, Subbarao Kambhampati, and Craig A. Knoblock, editors,
AIPS'00: Proceedings of the Fifth International Conference on
Artificial Intelligence Planning Systems (Breckenridge, CO, USA,
April14-17, 2000), pages 371-378, Menlo Park, CA, 2000. AAAI Press.
@inproceedings{schmid/wysotzki:2000d, author = {Ute Schmid and Fritz Wysotzki}, title = {Applying Inductive Programm Synthesis to Macro Learning}, editor = {Steve Chien and Subbarao Kambhampati and Craig A. Knoblock}, booktitle = {{AIPS'00}: Proceedings of the Fifth International Conference on Artificial Intelligence Planning Systems (Breckenridge, CO, USA, April\,14--17, 2000)}, year = 2000, pages = {371--378}, address = {Menlo Park, CA}, publisher = {{AAAI Press}}, isbn = {1-57735-111-8} }
-
Ute Schmid.
Adaptation of non-isomorphic sources in analogical problem solving.
In K. Holyoak, D. Gentner, and B. Kokinov, editors, Proceedings
of the Workshop Advances in Analogy Research: Integration of Theory and Data
from the Cognitive, Computational, and Neural Sciences (Sofia, Bulgarian,
July17-20, 1998), NBU Series in Cognitive Science, pages 406-407, Sofia,
1998. New Bulgarian University Press.
@inproceedings{schmid:1998, author = {Schmid, Ute}, title = {Adaptation of non-isomorphic sources in analogical problem solving}, editor = {Holyoak, K. and Gentner, D. and Kokinov, B.}, booktitle = {Proceedings of the Workshop Advances in Analogy Research: Integration of Theory and Data from the Cognitive, Computational, and Neural Sciences (Sofia, Bulgarian, July\,17--20, 1998)}, year = 1998, series = {NBU Series in Cognitive Science}, pages = {406--407}, address = {Sofia}, publisher = {New Bulgarian University Press} }
-
Ute Schmid.
Analogical problem solving by adaptation of schemes.
In F. E. Ritter and R. M. Young, editors, ECCM'98: Proceedings
of the 2nd European Conference on Cognitive Modelling (Nottingham, UK,
April1.-4, 1998). Nottingham University Press, 1998.
Poster.
@inproceedings{schmid:1998b, author = {Ute Schmid}, title = {Analogical Problem Solving by Adaptation of Schemes}, editor = {F. E. Ritter and R. M. Young}, booktitle = {{ECCM'98}: Proceedings of the 2nd European Conference on Cognitive Modelling (Nottingham, UK, April\,1.--4, 1998)}, year = 1998, publisher = {Nottingham University Press}, note = {Poster}, documenturl = {http://user.cs.tu-berlin.de/~schmid/pub-ps/eccm98-short.ps} }
-
Ute Schmid.
Iterative macro-operators revisited: Applying program synthesis to
learning in planning.
Technical Report CMU-CS-99-114, Computer Science Department, Carnegie
Mellon University, Pittsburg, PA, 1999.
@techreport{schmid:1999, author = {Ute Schmid}, title = {Iterative Macro-Operators Revisited: Applying Program Synthesis to Learning in Planning}, institution = {Computer Science Department, Carnegie Mellon University}, year = 1999, number = {CMU-CS-99-114}, address = {Pittsburg, PA} }
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Ute Schmid.
Inductive Synthesis of Functional Programs. Universal Planning,
Folding of Finite Programs, and Schema Abstraction by Analogical Reasoning,
volume 2654 of Lecture Notes in Artificial Intelligence.
Springer, Berlin/Heidelberg, 2003.
Ute Schmid's habilitation thesis. May2001, Department of Electrical
Engineering and Computer Science, TU Berlin.
@book{schmid:2003, author = {Ute Schmid}, title = {Inductive Synthesis of Functional Programs. Universal Planning, Folding of Finite Programs, and Schema Abstraction by Analogical Reasoning}, publisher = {Springer}, year = 2003, volume = 2654, series = {Lecture Notes in Artificial Intelligence}, address = {Berlin\,/\,Heidelberg}, note = {Ute Schmid's habilitation thesis. May\,2001, Department of Electrical Engineering and Computer Science, TU Berlin}, keywords = {book; inductive programming}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-40174-2}, url = {http://www.springerlink.com/content/mevxuj0c1q49/}, doi = {10.1007/b12055}, documenturl = {http://www.inf.uos.de/schmid/pub-ps/habil.ps.gz} }
-
Ute Schmid.
A Cognitive Model of Learning by Doing.
Models And Human Reasoning, pages 235-252, 2005.
@article{schmid:2005, author = {Ute Schmid}, title = {{A Cognitive Model of Learning by Doing}}, journal = {Models And Human Reasoning}, year = 2005, pages = {235--252}, publisher = {Wissenschaft \& Technik Verlag}, editor = {Bap, S. and Gulden, J. and Wieczorek, T.}, address = {Berlin} }
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Ute Schmid, Martin Mühlpfordt, and Fritz Wysotzki.
Induction of recursive program schemes as inference of context free
tree grammers.
Draft, 1998.
@unpublished{schmid_ea:1998, author = {Ute Schmid and Martin M{\"u}hlpfordt and Fritz Wysotzki}, title = {Induction of Recursive Program Schemes as Inference of Context Free Tree Grammers}, year = 1998, note = {Draft}, documenturl = {http://www.inf.uos.de/schmid/pub-ps/jml-article-draft.ps} }
-
Ute Schmid, R. Mercy, and Fritz Wysotzki.
Programming by analogy: Retrieval, mapping, adaptation and
generalization of recursive program schemes.
In FGML'98: Proceedings of the Annual Meeting of the GI
Machine Learning Group (Technische Universität, Berlin, Aug.17.-19,
1998), volume 98 of Forschungsberichte des Fachbereichs Informatik,
pages 140-147, TU Berlin, 1998.
Beiträge zum Treffen der GI-Fachgruppe 1.1.3 Maschinelles Lernen.
@inproceedings{schmid_ea:1998b, author = {Ute Schmid and R. Mercy and Fritz Wysotzki}, title = {Programming by analogy: Retrieval, Mapping, adaptation and generalization of recursive program schemes}, booktitle = {{FGML'98}: Proceedings of the {Annual Meeting of the GI Machine Learning Group} (Technische Universit\"at, Berlin, Aug.\,17.--19, 1998)}, year = 1998, series = {Forschungsberichte des Fachbereichs Informatik}, volume = 98, pages = {140--147}, address = {TU Berlin}, note = {Beitr{\"a}ge zum Treffen der GI-Fachgruppe 1.1.3 Maschinelles Lernen}, number = 11 }
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Ute Schmid, U. Sinha, and Fritz Wysotzki.
Generalizing recursive program schemes with anti-unification.
In GMD, editor, FGML'00: Proceedings of the Annual Meeting of
the GI Machine Learning Group (St.Augustin, 18.-20.09.2000), pages
139-140, 2000.
Beiträge zum Treffen der GI-Fachgruppe 1.1.3 Maschinelles Lernen.
@inproceedings{schmid_ea:2000, author = {Ute Schmid and U. Sinha and Fritz Wysotzki}, title = {Generalizing Recursive Program Schemes with Anti-Unification}, editor = {GMD}, booktitle = {{FGML'00}: Proceedings of the {Annual Meeting of the GI Machine Learning Group} (St.\,Augustin, 18.--20.\,09.\,2000)}, year = 2000, pages = {139--140}, note = {Beitr{\"a}ge zum Treffen der GI-Fachgruppe 1.1.3 Maschinelles Lernen} }
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Ute Schmid, Emanuel Kitzelmann, and Fritz Wysotzki.
Inductive program synthesis: From theory to application.
In Gabriella Kókai and Jens Zeidler, editors, FGML'02:
Proceedings of the Annual Meeting of the GI Machine Learning Group
(Hannover, Germany, Oct.7-9, 2002), pages 135-141, 2002.
Beiträge zum Treffen der GI-Fachgruppe 1.1.3 Maschinelles Lernen.
@inproceedings{schmid_ea:2002, author = {Ute Schmid and Emanuel Kitzelmann and Fritz Wysotzki}, title = {Inductive Program Synthesis: From Theory to Application}, editor = {Gabriella K\'okai and Jens Zeidler}, booktitle = {{FGML'02}: Proceedings of the {Annual Meeting of the GI Machine Learning Group (Hannover, Germany, Oct.\,7--9, 2002)}}, year = 2002, pages = {135--141}, note = {Beitr{\"a}ge zum Treffen der GI-Fachgruppe 1.1.3 Maschinelles Lernen}, keywords = {2002; automatic programming; induction; inductive; inductive functional programming; inductive inference; inductive learning; inductive program synthesis; inductive programming; inproceedings; machine learning; programming; recursive program schemes}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/publications/fgml02.pdf} }
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Ute Schmid, Martin Hofmann, and Emanuel Kitzelmann.
Analytical inductive programming as a cognitive rule acquisition
device.
In B. Goertzel, P. Hitzler, and M. Hutter, editors, Artificial
General Intelligence. AGI'09: Proceedings of the 2nd Conference on
Artificial General Intelligence (Arlington, Virginia, March6-9 2009),
Advances in Intelligent Systems Research, pages 162-167. Atlantis Press,
2009.
@inproceedings{schmid_ea:2009, author = {Ute Schmid and Martin Hofmann and Emanuel Kitzelmann}, title = {Analytical Inductive Programming as a Cognitive Rule Acquisition Device}, editor = {B. Goertzel and P. Hitzler and M. Hutter}, booktitle = {Artificial General Intelligence. {AGI'09}: Proceedings of the 2nd Conference on Artificial General Intelligence (Arlington, Virginia, March\,6--9 2009)}, year = 2009, series = {Advances in Intelligent Systems Research}, pages = {162--167}, publisher = {Atlantis Press}, isbn = {978-90-78677-24-6}, url = {http://dx.doi.org/10.2991/agi.2009.35}, keywords = {inductive programming}, abstract = {One of the most admirable characteristic of the human cognitive system is its ability to extract generalized rules covering regularities from example experience presented by or experienced from the environment. Humans' problem solving, reasoning and verbal behavior often shows a high degree of systematicity and productivity which can best be characterized by a competence level reflected by a set of recursive rules. While we assume that such rules are different for different domains, we believe that there exists a general mechanism to extract such rules from only positive examples from the environment. Our system Igor2 is an analytical approach to inductive programming which induces recursive rules by generalizing over regularities in a small set of positive input/output examples. We applied Igor2 to typical examples from cognitive do- mains and can show that the Igor2 mechanism is able to learn the rules which can best describe systematic and productive behavior in such domains.} }
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Ute Schmid, Emanuel Kitzelmann, and Rinus Plasmeijer, editors.
AAIP'09: Proceedings of the 3rd Workshop on Approaches and
Applications of Inductive Programming (ICFP'09, Edinburgh, Scottland,
Sept.4, 2009), number 81 in Bamberger Beiträge zur Wirtschaftsinformatik
und Angewandten Informatik. University of Bamberg, 2009.
In conjunction with the 14th ACM SIGPLAN International Conference
on Functional Programming (ICFP'09).
@proceedings{schmid_ea:2009b, title = {{AAIP'09}: Proceedings of the 3rd Workshop on Approaches and Applications of Inductive Programming ({ICFP'09}, Edinburgh, Scottland, Sept.\,4, 2009)}, year = 2009, editor = {Schmid, Ute and Kitzelmann, Emanuel and Plasmeijer, Rinus}, number = 81, series = {Bamberger Beitr\"age zur Wirtschaftsinformatik und Angewandten Informatik}, publisher = {University of Bamberg}, note = {In conjunction with the 14th {ACM} {SIGPLAN} International Conference on Functional Programming ({ICFP'09})}, size = {120 pages} }
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Ute Schmid, Martin Hofmann, and Emanuel Kitzelmann.
Inductive Programming. Example-driven Construction of Functional
Programs.
KI - Künstliche Intelligenz, 23(2):38-41, 2009.
@article{schmid_ea:2009c, author = {Ute Schmid and Martin Hofmann and Emanuel Kitzelmann}, title = {{Inductive Programming. Example-driven Construction of Functional Programs}}, journal = {KI -- K{\"u}nstliche Intelligenz}, year = 2009, volume = 23, number = 2, pages = {38--41}, documenturl = {http://www.kuenstliche-intelligenz.de/fileadmin/template/main/archiv/pdf/ki2009-02_page38_web_teaser.pdf} }
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Ute Schmid, Martin Hofmann, Florian Bader, Tilmann Häberle, and Thomas
Schneider.
Incident Mining using Structural Prototypes.
In Nicolás García-Pedrajas, Herrera Francisco, Colin Fyfe,
José Manuel Benítez, and Moonis Ali, editors, Trends in Applied
Intelligent Systems. 23rd International Conference on Industrial Engineering
and Other Applications of Applied Intelligent Systems, IEA/AIE'10, Cordoba,
Spain, June1-4, 2010. Proceedings, volume 6097 of Lecture Notes in
Computer Science. Lecture Notes in Artificial Intelligence, pages 327-336,
Berlin/Heidelberg, 2010. Springer.
@inproceedings{schmid_ea:2010, author = {Ute Schmid and Martin Hofmann and Florian Bader and Tilmann H{\"a}berle and Thomas Schneider}, title = {{Incident Mining using Structural Prototypes}}, editor = {Nicol{\'a}s Garc{\'i}a-Pedrajas and Herrera Francisco and Colin Fyfe and Jos{\'e} Manuel Ben{\'i}tez and Moonis Ali}, booktitle = {Trends in Applied Intelligent Systems. 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, {IEA/AIE'10}, Cordoba, Spain, June\,1--4, 2010. Proceedings}, year = 2010, series = {Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence}, volume = 6097, pages = {327--336}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, isbn = {978-3-642-13021-2} }
-
Ute Schmid, Emanuel Kitzelmann, and Rinus Plasmeijer, editors.
Approaches and Applications of Inductive Programming. 3rd
International Workshop, AAIP'09, Edinburgh, UK, Sept.4, 2009. Revised
Papers, volume 5812 of Lecture Notes in Computer Science,
Berlin/Heidelberg, 2010. Springer.
@proceedings{schmid_ea:2010b, title = {Approaches and Applications of Inductive Programming. 3rd International Workshop, {AAIP'09}, Edinburgh, UK, Sept.\,4, 2009. Revised Papers}, year = 2010, editor = {Ute Schmid and Emanuel Kitzelmann and Rinus Plasmeijer}, volume = 5812, series = {Lecture Notes in Computer Science}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-642-11930-9}, url = {http://www.springerlink.com/content/r4r654707444/}, doi = {10.1007/978-3-642-11931-6}, keywords = {functional programming; inductive programming} }
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Jürgen Schmidhuber.
Optimal ordered problem solver.
Machine Learning, 54(3):211-254, March 2004.
@article{schmidhuber:2004, author = {J\"urgen Schmidhuber}, title = {Optimal Ordered Problem Solver}, journal = {Machine Learning}, year = 2004, volume = 54, number = 3, pages = {211--254}, month = {March}, publisher = {Springer}, address = {Netherlands}, issn = {0885-6125 (Print) 1573-0565 (Online)}, url = {http://www.springerlink.com/content/l6v96242k51117w3/}, doi = {10.1023/B:MACH.0000015880.99707.b2}, keywords = {enumerative ip; induction; inductive programming; metalearning; oops; program synthesis}, abstract = {We introduce a general and in a certain sense time-optimal way of solving one problem after another, efficiently searching the space of programs that compute solution candidates, including those programs that organize and manage and adapt and reuse earlier acquired knowledge. The Optimal Ordered Problem Solver (OOPS) draws inspiration from Levin's Universal Search designed for single problems and universal Turing machines. It spends part of the total search time for a new problem on testing programs that exploit previous solution-computing programs in computable ways. If the new problem can be solved faster by copy-editing/invoking previous code than by solving the new problem from scratch, then OOPS will find this out. If not, then at least the previous solutions will not cause much harm. We introduce an efficient, recursive, backtracking-based way of implementing OOPS on realistic computers with limited storage. Experiments illustrate how OOPS can greatly profit from metalearning or metasearching, that is, searching for faster search procedures.} }
-
Jürgen Schmidhuber.
How to learn a program: Optimal universal learners & goedel machines.
In Emanuel Kitzelmann, Roland J. Olsson, and Ute Schmid, editors,
AAIP'05: Proceedings of the 1st Workshop on Approaches and
Applications of Inductive Programming (Bonn, Germany, Aug.7, 2005),
page 11, 2005.
Invited Talk Abstract.
@inproceedings{schmidhuber:2005, author = {J\"urgen Schmidhuber}, title = {How to Learn a Program: Optimal Universal Learners & Goedel Machines }, editor = {Emanuel Kitzelmann and Roland J. Olsson and Ute Schmid}, booktitle = {{AAIP'05}: Proceedings of the 1st Workshop on Approaches and Applications of Inductive Programming (Bonn, Germany, Aug.\,7, 2005)}, year = 2005, pages = 11, note = {Invited Talk Abstract}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/aaip05/proceedings/abs_schmidhuber.pdf} }
-
Uwe Schöning.
Logic for Computer Scientists.
Modern Birkhäuser Classics. Birkhäuser Boston, 2008.
@book{schoening:2008, author = {Uwe Sch\"{o}ning}, title = {Logic for Computer Scientists}, publisher = {Birkh\"{a}user Boston}, year = 2008, series = {Modern Birkh\"{a}user Classics}, keywords = {logic}, isbn = 0817647627 }
-
Stefan Schrödl and Stefan Edelkamp.
Inferring flow of control in program synthesis by example.
In KI-99: Advances in Artificial Intelligence. 23rd Annual
German Conference on Artificial Intelligence, Bonn, Germany, Sept.13-15,
1999. Proceedings, volume 1701 of Lecture Notes in Computer Science.
Lecture Notes in Artificial Intelligence, pages 171-182,
Berlin/Heidelberg, 1999. Springer.
@inproceedings{schroedl/edelkamp:1999, author = {Stefan Schr{\"o}dl and Stefan Edelkamp}, title = {Inferring Flow of Control in Program Synthesis by Example}, booktitle = {{KI-99}: Advances in Artificial Intelligence. 23rd Annual German Conference on Artificial Intelligence, Bonn, Germany, Sept.\,13--15, 1999. Proceedings}, year = 1999, series = {Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence}, volume = 1701, pages = {171--182}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-66495-6}, url = {http://www.springerlink.com/content/dqcw6kjnmw3gdwh5/}, abstract = {Abstract. We present a supervised, interactive learning technique that infers control structures of computer programs from user-demonstrated traces. A two-stage process is applied: first, a minimal deterministic finite automaton (DFA)Mlabeled by the instructions of the program is learned from a set of example traces and membership queries to the user. It accepts all preffixes of traces of the target program. The number of queries is bounded byO(k|M|), withkbeing the total number of instructions in the initial example traces. In the second step we parse this automaton into a high-level programming language inO(|M|2) steps, replacing jumps by conditional control structures.}, doi = {10.1007/3-540-48238-5_14} }
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Ehud Y. Shapiro.
An algorithm that infers theories from facts.
In A. Drinan, editor, IJCAI'81: Proceedings of the 7th
International Joint Conference on Artificial Intelligence (Vancouver, BC,
Canada, Aug.24-28, 1981), pages 446-451, Los Altos, CA, 1981. Morgan
Kaufmann.
@inproceedings{shapiro:1981, author = {Ehud Y. Shapiro}, title = {An Algorithm that Infers Theories from Facts}, editor = {A. Drinan}, booktitle = {{IJCAI}'81: Proceedings of the 7th International Joint Conference on Artificial Intelligence (Vancouver, BC, Canada, Aug.\,24--28, 1981)}, year = 1981, pages = {446--451}, address = {Los Altos, CA}, publisher = {Morgan Kaufmann}, keywords = {ilp; inductive programming; machine learning; mis; seminal paper}, annote = {short version of the tech-report: Inductive Inference of Theories from Facts, 1981, Yale Univ.} }
-
Ehud Y. Shapiro.
Algorithmic Program Debugging.
MIT Press, 1983.
@book{shapiro:1983, author = {Ehud Y. Shapiro}, title = {Algorithmic Program Debugging}, publisher = {MIT Press}, year = 1983, keywords = {book; debugging; ilp; mis}, annote = {Shapiro's PhD dissertation} }
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Jude W. Shavlik.
Acquiring recursive and iterative concepts with explanation-based
learning.
Machine Learning, 5(1):39-70, March 1990.
@article{shavlik:1990, author = {Jude W. Shavlik}, title = {Acquiring recursive and iterative concepts with explanation-based learning}, journal = {Machine Learning}, year = 1990, volume = 5, number = 1, pages = {39--70}, month = {March}, publisher = {Springer}, address = {Netherlands}, issn = {0885-6125 (Print) 1573-0565 (Online)}, url = {http://www.springerlink.com/content/l09626h1ng137737/}, abstract = {Inexplanation-based learning, a specific problem''s solution is generalized into a form that can be later used to solve conceptually similar problems. Most research in explanation-based learning involves relaxing constraints on the variables in the explanation of a specific example, rather than generalizing thegraphical structureof the explanation itself. However, this precludes the acquisition of concepts where an iterative or recursive process is implicitly represented in the explanation by a fixed number of applications. This paper presents an algorithm that generalizes explanation structures and reports empirical results that demonstrate the value of acquiring recursive and iterative concepts. The BAGGER2 algorithm learns recursive and iterative concepts, integrates results from multiple examples, and extracts useful subconcepts during generalization. On problems where learning a recursive rule is not appropriate, the system produces the same result as standard explanation-based methods. Applying the learned recursive rules only requires a minor extension to a PROLOG-like problem solver, namely, the ability to explicitly call a specific rule. Empirical studies demonstrate that generalizing the structure of explanations helps avoid the recently reported negative effects of learning.}, doi = {10.1023/A:1022659708512}, keywords = {Explanation-based generalization; generalizing explanation structures; generalizing to N; generalizing number; utility of learning; operationality versus generality} }
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D. Shaw, W. Swartout, and C. Green.
Inferring LISP programs from examples.
In IJCAI'75: Advance Papers of the 4th International Joint
Conference on Artificial Intelligence (Tbilisi, Georgia, USSR,Sept.3-8,
1975), pages 260-267, 1975.
@inproceedings{shaw_ea:1975, author = {D. Shaw and W. Swartout and C. Green}, title = {Inferring {LISP} Programs from Examples}, booktitle = {{IJCAI}'75: Advance Papers of the 4th International Joint Conference on Artificial Intelligence (Tbilisi, Georgia, USSR,Sept.\,3--8, 1975)}, year = 1975, pages = {260--267}, documenturl = {http://dli.iiit.ac.in/ijcai/IJCAI-75-VOL-1&2/PDF/037.pdf}, keywords = {ifp; induction; inductive programming; lisp; pre-summers; program synthesis} }
-
Tim Sheard and Leonidas Fegaras.
A fold for all seasons.
In FPCA'93: Proceedings of the 6th ACM SIGPLAN/SIGARCH
International Conference on Functional Programming Languages and Computer
Architecture (Copenhagen, Denmark, June9-11, 1993). ACM Press, 1993.
@inproceedings{sheard/fegaras:1993, author = {Tim Sheard and Leonidas Fegaras}, title = {A Fold for All Seasons}, booktitle = {{FPCA'93}: Proceedings of the 6th {ACM} {SIGPLAN/SIGARCH} International Conference on Functional Programming Languages and Computer Architecture (Copenhagen, Denmark, June\,9--11, 1993)}, year = 1993, publisher = {ACM Press}, isbn = {0-89791-595-X}, annote = {ute-inflit} }
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L. Siklossy and D. A. Sykes.
Automatic program synthesis from example problems.
In IJCAI'75: Advance Papers of the 4th International Joint
Conference on Artificial Intelligence (Tbilisi, Georgia, USSR,Sept.3-8,
1975), pages 268-273, 1975.
@inproceedings{siklossy/sykes:1975, author = {L. Siklossy and D. A. Sykes}, title = {Automatic Program Synthesis from Example Problems}, booktitle = {{IJCAI}'75: Advance Papers of the 4th International Joint Conference on Artificial Intelligence (Tbilisi, Georgia, USSR,Sept.\,3--8, 1975)}, year = 1975, pages = {268--273}, documenturl = {http://dli.iiit.ac.in/ijcai/IJCAI-75-VOL-1&2/PDF/038.pdf}, keywords = {ifp; induction; inductive programming; lisp; pre-summers; program synthesis} }
-
A. Smaill and I. Green.
Automating the synthesis of functional programs, 1995.
@misc{smaill/green:1995, author = {A. Smaill and I. Green}, title = {Automating the synthesis of functional programs}, year = 1995, institution = {Department of Artificial Intelligence, University of Edinburgh}, number = {Research paper 777}, annote = {ute-inflit} }
-
Douglas R. Smith.
The synthesis of LISP programs from examples: A survey.
In Alan W. Biermann, Yves Kodratoff, and Gérard Guiho, editors,
Automatic Program Construction Techniques, pages 307-324. The Free
Press, New York, NY, USA, 1984.
@incollection{smith:1984, author = {Smith, Douglas R.}, title = {The Synthesis of {LISP} Programs from Examples: A Survey}, editor = {Alan W. Biermann and Yves Kodratoff and G\'erard Guiho}, booktitle = {Automatic Program Construction Techniques}, publisher = {The Free Press}, year = 1984, pages = {307--324}, address = {New York, NY, USA}, isbn = 0029490707, keywords = {analytical ip; comparison; enumerative ip; ifp; induction; inductive programming; program synthesis; survey}, annote = {a good survey of classical inductive synthesis from traces, summers, biermann etc.} }
-
E. Soloway and J. C. Spohrer, editors.
Studying the Novice Programmer.
Lawrence Erlbaum, Hillsdale, NJ, 1989.
@book{soloway/spohrer:1989, editor = {E. Soloway and J. C. Spohrer}, title = {Studying the Novice Programmer}, publisher = {Lawrence Erlbaum}, year = 1989, address = {Hillsdale, NJ} }
-
Irene Stahl and Irene Weber.
The arguments of newly invented predicates in ILP.
In ILP'94: Proceedings of the 4th International Workshop on
Inductive Logic Programming (Bonn, Germany, Sept.12-14, 1994), volume 237
of GMD-Studien. Gesellschaft für Mathematik und
Datenverarbeitung MBH, 1994.
@inproceedings{stahl/weber:1994, author = {Irene Stahl and Irene Weber}, title = {The Arguments of Newly Invented Predicates in {ILP}}, booktitle = {{ILP'94}: Proceedings of the 4th International Workshop on Inductive Logic Programming (Bonn, Germany, Sept.\,12--14, 1994)}, year = 1994, series = {{GMD}-Studien}, volume = 237, publisher = {{G}esellschaft f{\"{u}}r {M}athematik und {D}atenverarbeitung {MBH}}, keywords = {ilp; induction; inductive programming; predicate invention; program synthesis} }
-
Irene Stahl.
Predicate invention in ilp - an overview.
In Pavel Brazdil, editor, Machine Learning: ECML-93. European
Conference on Machine Learning Vienna, Austria, April5-7, 1993.
Proceedings, volume 667 of Lecture Notes in Computer Science, pages
311-322. Springer, 1993.
@inproceedings{stahl:1993, author = {Irene Stahl}, title = {Predicate invention in ILP -- an overview}, editor = {Pavel Brazdil}, booktitle = {Machine Learning: {ECML-93}. European Conference on Machine Learning Vienna, Austria, April\,5--7, 1993. Proceedings}, year = 1993, series = {Lecture Notes in Computer Science}, volume = 667, pages = {311--322}, publisher = {Springer}, keywords = {ilp; induction; inductive programming; overview; predicate invention; program synthesis}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-56602-1}, url = {http://www.springerlink.com/content/70510v0l339q226j/}, abstract = {Inductive Logic Programming (ILP) is a subfield of machine learning dealing with inductive inference in a first order Horn clause framework. A problem in ILP is how to extend the hypotheses language in the case that the vocabulary given initially is insufficient. One way to adapt the vocabulary is to introducenew predicates.}, doi = {10.1007/3-540-56602-3_144} }
-
Irene Stahl.
On the utility of predicate invention in inductive logic programming.
In Francesco Bergadano and Luc De Raedt, editors, Machine
Learning: ECML-94. European Conference on Machine Learning, Catania, Italy,
April6-8, 1994. Proceedings, volume 784 of Lecture Notes in Computer
Science, pages 272-286, Berlin/Heidelberg, 1994. Springer.
@inproceedings{stahl:1994, author = {Irene Stahl}, title = {On the utility of predicate invention in inductive logic programming}, editor = {Bergadano, Francesco and De~Raedt, Luc}, booktitle = {Machine Learning: {ECML-94}. European Conference on Machine Learning, Catania, Italy, April\,6--8, 1994. Proceedings}, year = 1994, series = {Lecture Notes in Computer Science}, volume = 784, pages = {272--286}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-57868-0}, url = {http://www.springerlink.com/content/f021737t2325313p/}, abstract = {The task of predicate invention in ILP is to extend the hypothesis language with new predicates in case that the vocabulary given initially is insufficient for the learning task. However, whether predicate invention really helps to make learning succeed in the extended language depends on the bias that is currently employed.}, doi = {10.1007/3-540-57868-4_64} }
-
Irene Stahl.
The appropriateness of predicate invention as bias shift operation in
ILP.
Machine Learning, 20(1-2):95-117, July 1995.
@article{stahl:1995, author = {Irene Stahl}, title = {The Appropriateness of Predicate Invention as Bias Shift Operation in {ILP}}, journal = {Machine Learning}, year = 1995, volume = 20, number = {1-2}, pages = {95--117}, month = {July}, keywords = {Inductive Logic Programming; Bias Shift; Predicate Invention}, publisher = {Springer}, address = {Netherlands}, issn = {0885-6125 (Print) 1573-0565 (Online)}, url = {http://www.springerlink.com/content/k322175786h1j628/}, abstract = {The task of predicate invention in Inductive Logic Programming is to extend the hypothesis language with new predicates if the vocabulary given initially is insufficient for the learning task. However, whether predicate invention really helps to make learning succeed in the extended language depends on the language bias currently employed.In this paper, we investigate for which commonly employed language biases predicate invention is an appropriate shift operation. We prove that for some restricted languages predicate invention does not help when the learning task fails and we characterize the languages for which predicate invention is useful. We investigate the decidability of the bias shift problem for these languages and discuss the capabilities of predicate invention as a bias shift operation.}, doi = {10.1023/A:1022638219164} }
-
Irene Stahl.
Predicate invention in inductive logic programming.
In Luc De Raedt, editor, Advances in Inductive Logic
Programming, pages 34-47. IOS Press, 1996.
@incollection{stahl:1996, author = {Irene Stahl}, title = {Predicate Invention in Inductive Logic Programming}, editor = {De~Raedt, Luc}, booktitle = {Advances in Inductive Logic Programming}, publisher = {IOS Press}, year = 1996, pages = {34--47}, keywords = {ilp; induction; inductive programming; overview; predicate invention; program synthesis} }
-
Wolfgang Stolzmann.
An introduction to anticipatory classifier systems.
In Learning Classifier Systems. From Foundations to
Applications, volume 1813 of Lecture Notes in Computer Science. Lecture
Notes in Artificial Intelligence, pages 175-194. Springer,
Berlin/Heidelberg, 2000.
@incollection{stolzmann:2000, author = {Wolfgang Stolzmann}, title = {An Introduction to Anticipatory Classifier Systems}, booktitle = { Learning Classifier Systems. From Foundations to Applications}, publisher = {Springer}, year = 2000, volume = 1813, series = {Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence}, pages = {175--194}, address = {Berlin\,/\,Heidelberg}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-67729-1}, url = {http://www.springerlink.com/content/gclp9mtkkggk0vhv/}, doi = {10.1007/3-540-45027-0_9}, keywords = {acs}, abstract = {Anticipatory Classifier Systems (ACS) are classifier systems that learn by using the cognitive mechanism of anticipatory behavioral control which was introduced in cognitive psychology by Hoffmann [4]. They can learn in deterministic multi-step environments.1 A stepwise introduction to ACS is given. We start with the basic algorithm and apply it in simple ``woods'' environments. Itwill be shown that this algorithm can only learn in a special kind of deterministic multi-step environments. Two extensionsare discussed. The first one enables an ACS to learn in any deterministic multi-step environment. The second one allows anACS to deal with a special kind of non-Markov state.} }
-
Phillip D. Summers.
Program Construction from Examples.
PhD thesis, Department of Computer Science, Yale University, New
Haven, US-CT, 1975.
@phdthesis{summers:1975, author = {Phillip D. Summers}, title = {Program Construction from Examples}, school = {Department of Computer Science, Yale University}, year = 1975, address = {New Haven, US-CT}, keywords = {analytical ip; ifp; induction; inductive programming; ip-system; lisp; program synthesis; thesys} }
-
Phillip D. Summers.
A methodology for LISP program construction from examples.
Journal of the ACM, 24(1):161-175, January 1977.
@article{summers:1977, author = {Phillip D. Summers}, title = {A Methodology for {LISP} Program Construction from Examples}, journal = {Journal of the {ACM}}, year = 1977, volume = 24, number = 1, pages = {161--175}, month = {January}, address = {New York, NY, USA}, publisher = {{ACM}}, url = {http://doi.acm.org/10.1145/321992.322002}, keywords = {analytical ip; article; ifp; induction; inductive programming; program synthesis; seminal paper; thesys}, annote = {The inductive programming seminal paper from Summers. Constructing a linear recursive program by generalising regularities in a finite set of traces and predicates.}, abstract = {An automatic programming system, THESYS, for constructing recursive LISP programs from examples of what they do is described. The construction methodology is illustrated as a series of transformations from the set of examples to a program satisfying the examples. The transformations consist of (1) deriving the specific computation associated with a specific example, (2) deriving control flow predicates, and (3) deriving an equivalent program specification in the form of recurrence relations. Equivalence between certain recurrence relations and various program schemata is proved. A detailed description of the construction of four programs is presented to illustrate the application of the methodology.} }
-
Lappoon R. Tang, Mary E Califf, and Raymond J. Mooney.
An experimental comparison of genetic programming and inductive logic
programming on learning recursive list functions.
Technical Report AI-98-271, University of Texas at Austin, Austin,
TX, USA, 1998.
@techreport{tang_ea:1998, author = {Lappoon R. Tang and Mary E Califf and Raymond J. Mooney}, title = {An Experimental Comparison of Genetic Programming and Inductive Logic Programming on Learning Recursive List Functions}, institution = {University of Texas at Austin}, year = 1998, number = {AI-98-271}, address = {Austin, TX, USA}, documenturl = {http://www.cs.utexas.edu/~ml/papers/ilpgp-ml-98.pdf}, keywords = {comparison; enumerative ip; experiment; gp; ifp; ilp; induction; inductive programming; program evolution; program synthesis}, abstract = {This paper experimentally compares three approaches to program induction: inductive logic programming (ILP), genetic programming (GP), and genetic logic programming (GLP) (a variant of GP for inducing Prolog programs). Each of these methods was used to induce four simple, recursive, list-manipulation functions. The results indicate that ILP is the most likely to induce a correct program from small sets of random examples, while GP is generally less accurate. GLP performs the worst, and is rarely able to induce a correct program. Interpretations of these results in terms of differences in search methods and inductive biases are presented.} }
-
Terese.
Term Rewriting Systems, volume 55 of Cambridge Tracts in
Theoretical Computer Science.
Cambridge University Press, 2003.
@book{terese:2003, author = {Terese}, title = {Term Rewriting Systems}, publisher = {Cambridge University Press}, year = 2003, volume = 55, series = {Cambridge Tracts in Theoretical Computer Science}, keywords = {book; term rewriting} }
-
J. Toussaint, Ute Schmid, and Fritz Wysotzki.
Using recursive control rules in planning.
In H. R. Arabnia, editor, ICAI'10: Proceedings of the 12th
International Conference on Artificial Intelligence (Las Vegas, Nevada, USA,
July12-15, 2010), volume 2, pages 1012-1015, Las Vegas, 2001. CSREA
Press.
@inproceedings{toussaint_ea:2001, author = {J. Toussaint and Ute Schmid and Fritz Wysotzki}, title = {Using Recursive Control Rules in Planning}, editor = {H. R. Arabnia}, booktitle = {{ICAI'10}: Proceedings of the 12th International Conference on Artificial Intelligence (Las Vegas, Nevada, USA, July\,12--15, 2010)}, year = 2001, volume = 2, pages = {1012--1015}, address = {Las Vegas}, publisher = {{CSREA} Press} }
-
Paul E. Utgoff.
Shift of bias for inductive concept learning.
In Ryszard S. Michalski, Jaime G. Carbonell, and Tom M. Mitchell,
editors, Machine Learning. An Artificial Intelligence Approach,
volume 2, chapter 5, pages 107-148. Morgan Kaufmann, Los Altos, CA, 1986.
@incollection{utgoff:1986, author = {Paul E. Utgoff}, title = {Shift of Bias for Inductive Concept Learning}, editor = {Ryszard S. Michalski and Jaime G. Carbonell and Tom M. Mitchell}, booktitle = {Machine Learning. An Artificial Intelligence Approach}, publisher = {Morgan Kaufmann}, year = 1986, volume = 2, chapter = 5, pages = {107--148}, address = {Los Altos, CA}, keywords = {bias; bias-shift; machine learning} }
-
Tarmo Uustalu, Varmo Vene, and Alberto Pardo.
Recursion schemes from comonads.
Nordic Journal of Computing, 8(3):366-390, 2001.
@article{uustalu_ea:2001, author = {Uustalu, Tarmo and Vene, Varmo and Pardo, Alberto}, title = {Recursion schemes from comonads}, journal = {Nordic Journal of Computing}, year = 2001, volume = 8, number = 3, pages = {366--390}, address = {Finland}, issn = {1236-6064}, publisher = {Publishing Association Nordic Journal of Computing} }
-
L. G. Valiant.
A theory of the learnable.
Communications of the ACM, 27(11):1134-1142, 1984.
@article{valiant:1984, author = {L. G. Valiant}, title = {A Theory of the Learnable}, journal = {Communications of the {ACM}}, year = 1984, volume = 27, number = 11, pages = {1134--1142}, address = {New York, NY, USA}, publisher = {{ACM}}, url = {http://doi.acm.org/10.1145/1968.1972}, keywords = {induction; machine learning; pac-learning; seminal paper}, annote = {Valiants seminal paper on computational learning theory.} }
-
Antonio Varlaro, Margherita Berardi, and Donato Malerba.
Learning recursive theories with the separate-and-parallel conquer
strategy.
In Proceedings of the Workshop on Advances in Inductive Rule
Learning (Pisa, Italy, Sept.20-24, 2004), pages 179-193, 2004.
In conjunction with ECML/PKDD.
@inproceedings{varlaro_ea:2004, author = {Varlaro, Antonio and Berardi, Margherita and Malerba, Donato}, title = {Learning recursive theories with the separate-and-parallel conquer strategy}, booktitle = {Proceedings of the Workshop on Advances in Inductive Rule Learning (Pisa, Italy, Sept.\,20--24, 2004)}, year = 2004, pages = {179--193}, note = {In conjunction with ECML/PKDD} }
-
Geir Vattekar.
ADATE User Manual, March 2006.
@manual{vattekar:2006, author = {Geir Vattekar}, title = {ADATE User Manual}, month = {March}, year = 2006, school = {\O stfold University College} }
-
B. Wegbreit.
Goal-directed program transformation.
IEEE Transactions on Software Engineering, 2(2):69-80, 1976.
@article{wegbreit:1976, author = {B. Wegbreit}, title = {Goal-Directed Program Transformation}, journal = {IEEE Transactions on Software Engineering}, year = 1976, volume = 2, number = 2, pages = {69--80}, address = {Los Alamitos, CA, USA}, publisher = {IEEE Computer Society}, keywords = {program transformation}, url = {http://doi.ieeecomputersociety.org/10.1109/TSE.1976.233533}, abstract = {Program development often proceeds by transforming simple, clear programs into complex, involuted, but more efficient ones. This paper examines ways this process can be rendered more systematic. We show how analysis of program performance, partial evaluation of functions, and abstraction of recursive function definitions from recurring subgoals can be combined to yield many global transformations in a methodical fashion. Examples are drawn from compiler optimization, list processing, very high-evel languages, and APL execution.} }
-
Donald S. Williams.
Computer program organization induced from problem examples.
In Herbert A. Simon and Laurent Siklossy, editors,
Representation and Meaning: Experiments with Information Processing Systems,
chapter 4, pages 143-206. Prentice-Hall, Englewood Cliffs, NJ, 1972.
@incollection{williams:1972, author = {Donald S. Williams}, title = {Computer program organization induced from problem examples}, editor = {Herbert A. Simon and Laurent Siklossy}, booktitle = {Representation and Meaning: Experiments with Information Processing Systems}, publisher = {Prentice-Hall}, year = 1972, chapter = 4, pages = {143--206}, address = {Englewood Cliffs, NJ} }
-
R. S. Williams.
Learning to program by examining and modifying cases.
In John E. Laird, editor, ICML'88: Proceedings of the 5th
International Conference on Machine Learning (Ann Arbor, Michigan, USA,
June12-14, 1988), pages 318-324. Morgan Kaufmann, 1988.
@inproceedings{williams:1988, author = {R. S. Williams}, title = {Learning to program by examining and modifying cases}, editor = {John E. Laird}, booktitle = {{ICML'88}: Proceedings of the 5th International Conference on Machine Learning (Ann Arbor, Michigan, USA, June\,12--14, 1988)}, year = 1988, pages = {318--324}, publisher = {Morgan Kaufmann}, isbn = {0-934613-64-8}, annote = {ute-inflit} }
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R. S. Williams.
Learning to program by examining and modifying cases.
In J. L. Kolodner, editor, Proceedings of the DARPA Workshop on
Case-Based Reasoning (San Mateo, CAL, May 1988), pages 463-474. Morgan
Kaufmann, 1988.
@inproceedings{williams:1988b, author = {R. S. Williams}, title = {Learning to program by examining and modifying cases}, editor = {J. L. Kolodner}, booktitle = {Proceedings of the DARPA Workshop on Case-Based Reasoning (San Mateo, CAL, May 1988)}, year = 1988, pages = {463--474}, publisher = {Morgan Kaufmann} }
-
Man Wong and Tuen Mun.
Evolving recursive programs by using adaptive grammar based genetic
programming.
Genetic Programming and Evolvable Machines, 6(4):421-455,
December 2005.
@article{wong/mun:2005, author = {Man Wong and Tuen Mun}, title = {Evolving Recursive Programs by Using Adaptive Grammar Based Genetic Programming}, journal = {Genetic Programming and Evolvable Machines}, year = 2005, volume = 6, number = 4, pages = {421--455}, month = {December}, publisher = {Springer}, address = { etherlands}, issn = {1389-2576 (Print) 1573-7632 (Online)}, url = {http://www.springerlink.com/content/y66h33rp510w43l4/}, doi = {10.1007/s10710-005-4805-8}, keywords = {recursive programs; logic grammars; grammar based genetic programming; enumerative ip; gbgp; gp; induction; inductive programming; program evolution; program synthesis}, abstract = {Genetic programming (GP) extends traditional genetic algorithms to automatically induce computer programs. GP has been applied in a wide range of applications such as software re-engineering, electrical circuits synthesis, knowledge engineering, anddata mining. One of the most important and challenging research areas in GP is the investigation of ways to successfully evolverecursive programs. A recursive program is one that calls itself either directly or indirectly through other programs. Becauserecursions lead to compact and general programs and provide a mechanism for reusing program code, they facilitate GP to solvelarger and more complicated problems. Nevertheless, it is commonly agreed that the recursive program learning problem is verydifficult for GP. In this paper, we propose techniques to tackle the difficulties in learning recursive programs. The techniquesare incorporated into an adaptive Grammar Based Genetic Programming system (adaptive GBGP). A number of experiments have beenperformed to demonstrate that the system improves the effectiveness and efficiency in evolving recursive programs.} }
-
Stefan Wrobel.
First order theory refinement.
In Luc De Raedt, editor, Advances in Inductive Logic
Programming, pages 14-33. IOS Press, 1996.
@incollection{wrobel:1996, author = {Stefan Wrobel}, title = {First Order Theory Refinement}, editor = {De~Raedt, Luc}, booktitle = {Advances in Inductive Logic Programming}, publisher = {IOS Press}, year = 1996, pages = {14--33}, keywords = {ilp; theory revision} }
-
Fritz Wysotzki and Ute Schmid.
Synthesis of recursive programs from finite examples by detection of
macro-functions.
Technical Report 1-2, TU Berlin, Berlin, 2001.
@techreport{wysotzki/schmid:2001, author = {Wysotzki, Fritz and Schmid, Ute}, title = {Synthesis of Recursive Programs from Finite Examples by Detection of Macro-Functions}, institution = {TU Berlin}, year = 2001, number = {1--2}, address = {Berlin} }
-
Fritz Wysotzki.
Representation and induction of infinite concepts and recursive
action sequences.
In Alan Bundy, editor, IJCAI'83: Proceedings of the 8th
International Joint Conference on Artificial Intelligence (Karlsruhe,
Germany, Aug.,1983), pages 409-414. Morgan Kaufmann, 1983.
@inproceedings{wysotzki:1983, author = {Fritz Wysotzki}, title = {Representation and induction of infinite concepts and recursive action sequences}, editor = {Alan Bundy}, booktitle = {{IJCAI}'83: Proceedings of the 8th International Joint Conference on Artificial Intelligence (Karlsruhe, Germany, Aug.,1983)}, year = 1983, pages = {409--414}, publisher = {Morgan Kaufmann} }
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Fritz Wysotzki.
Program synthesis by hierarchical planning.
In P. Jorrand and V. Sgurev, editors, Artificial Intelligence:
Methodology, Systems, Applications, pages 3-11. Elsevier, Amsterdam, 1987.
@incollection{wysotzki:1987, author = {Fritz Wysotzki}, title = {Program synthesis by hierarchical planning}, editor = {P. Jorrand and V. Sgurev}, booktitle = {Artificial Intelligence: Methodology, Systems, Applications}, publisher = {Elsevier}, year = 1987, pages = {3--11}, address = {Amsterdam}, annote = {ute-inflit} }
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Fritz Wysotzki.
Development of inductive synthesis of functional programs.
In Emanuel Kitzelmann, Roland J. Olsson, and Ute Schmid, editors,
AAIP'05: Proceedings of the 1st Workshop on Approaches and
Applications of Inductive Programming (Bonn, Germany, Aug.7, 2005),
page 13, 2005.
Invited Talk Abstract.
@inproceedings{wysotzki:2005, author = {Fritz Wysotzki}, title = {Development of Inductive Synthesis of Functional Programs}, editor = {Emanuel Kitzelmann and Roland J. Olsson and Ute Schmid}, booktitle = {{AAIP'05}: Proceedings of the 1st Workshop on Approaches and Applications of Inductive Programming (Bonn, Germany, Aug.\,7, 2005)}, year = 2005, pages = 13, note = {Invited Talk Abstract}, documenturl = {http://www.cogsys.wiai.uni-bamberg.de/aaip05/proceedings/abs_wysotzki.pdf} }
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Alexey Rodriguez Yakushev and Johan Jeuring.
Enumerating well-typed terms generically.
In Ute Schmid, Emanuel Kitzelmann, and Rinus Plasmeijer, editors,
Approaches and Applications of Inductive Programming. 3rd International
Workshop, AAIP'09, Edinburgh, UK, Sept.4, 2009. Revised Papers, volume
5812 of Lecture Notes in Computer Science, pages 93-116,
Berlin/Heidelberg, 2010. Springer.
@inproceedings{yakushev/jeuring:2010, author = {Alexey Rodriguez Yakushev and Johan Jeuring}, title = {Enumerating Well-Typed Terms Generically}, editor = {Ute Schmid and Emanuel Kitzelmann and Rinus Plasmeijer}, booktitle = {Approaches and Applications of Inductive Programming. 3rd International Workshop, {AAIP'09}, Edinburgh, UK, Sept.\,4, 2009. Revised Papers}, year = 2010, series = {Lecture Notes in Computer Science}, volume = 5812, pages = {93--116}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-642-11930-9}, url = {http://www.springerlink.com/content/m921756m170166p3/}, abstract = {We use generic programming techniques to generate well-typed lambda terms. We encode well-typed terms by means of generalized algebraic datatypes (GADTs) and existential types. The Spine approach to generic programming supports GADTs, but it does not support the definition of generic producers for existentials. We describe how to extend the Spine approach to support existentials and we use the improved Spine to define a generic enumeration function. We show that the enumeration function can be used to generate the terms of simply typed lambda calculus.}, doi = {10.1007/978-3-642-11931-6_5}, documenturl = {http://www.springerlink.com/content/m921756m170166p3/fulltext.pdf} }
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Akihiro Yamamoto.
Which hypotheses can be found with inverse entailment?
In Nada Lavrač and Sašo Džeroski, editors,
Inductive Logic Programming. 7th International Workshop, ILP'97, Prague,
Czech Republic, Sept.17-20, 1997, Proceedings, volume 1297 of
Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence,
pages 296-308, Berlin/Heidelberg, 1997. Springer.
@inproceedings{yamamoto:1997, author = {Akihiro Yamamoto}, title = {Which Hypotheses Can Be Found with inverse Entailment?}, editor = {Nada Lavra{\v{c}} and Sa{\v{s}}o D{\v{z}}eroski}, booktitle = {Inductive Logic Programming. 7th International Workshop, {ILP'97}, Prague, Czech Republic, Sept.\,17--20, 1997, Proceedings}, year = 1997, series = {Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence}, volume = 1297, pages = {296--308}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-63514-7}, url = {http://www.springerlink.com/content/p368g628l6365821/}, abstract = {In this paper we give a completeness theorem of an inductive inference ruleinverse entailmentproposed by Muggleton. Our main result is that a hypothesis clauseHcan be derived from an exampleEunder a background theoryBwith inverse entailment iffHsubsumesErelative toBin Plotkin's sense. The theoryBcan be any clausal theory, and the exampleEcan be any clause which is neither a tautology nor implied byB. The derived hypothesisHis a clause which is not always definite. In order to prove the result we give a declarative semantics for arbitrary consistent clausal theories, and show that SB-resolution, which was originally introduced by Plotkin, is a complete procedural semantics. The completeness is shown as an extension of the completeness theorem of SLD-resolution. We also show that every hypothesisHderived with saturant generalization, proposed by Rouveirol, must subsume E w.r.t.Bin Buntine's sense. Moreover we show that saturant generalization can be obtained from inverse entailment by giving some restriction to it.}, doi = {10.1007/3540635149_58} }
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Qiang Yang, Rong Pan, and Sinno Jialin Pan.
Learning recursive HTN-method structures for planning.
In Proceedings of the Workshop on Artificial Intelligence
Planning and Learning (Providence, Rhode Island, USA, Sept.22, 2007),
2007.
In conjunction with the International Conference on Automated
Planning and Scheduling (ICAPS'07).
@inproceedings{yang_ea:2007, author = {Qiang Yang and Rong Pan and Sinno Jialin Pan}, title = {Learning Recursive {HTN}-Method Structures for Planning}, booktitle = {Proceedings of the Workshop on Artificial Intelligence Planning and Learning (Providence, Rhode Island, USA, Sept.\,22, 2007)}, year = 2007, note = {In conjunction with the International Conference on Automated Planning and Scheduling ({ICAPS'07})}, url = {http://www.cs.umd.edu/~ukuter/icaps07aipl/}, keywords = {learning-and-planning planning read} }
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Serap Yilmaz.
Inductive synthesis of recursive logic programs.
Master's thesis, University of Bilkent, Computer Science Department,
1997.
@mastersthesis{yilmaz:1997, author = {Serap Yilmaz}, title = {Inductive Synthesis of Recursive Logic Programs}, school = {University of Bilkent, Computer Science Department}, year = 1997, keywords = {Dialogs-II} }
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Tina Yu and Chris Clack.
PolyGP: A polymorphic genetic programming system in haskell.
In GP'98: Proceedings of the 3rd Conference on Genetic
Programming (Madison, Wisconsin, July22-25, 1998), pages 416-427. Morgan
Kaufmann, 1998.
The annual GP conference is now part of the GECCO conference.
@inproceedings{yu/clack:1998, author = {Tina Yu and Chris Clack}, title = {Poly{GP}: {A} Polymorphic Genetic Programming System in Haskell}, booktitle = {{GP'98}: Proceedings of the 3rd Conference on Genetic Programming (Madison, Wisconsin, July\,22--25, 1998)}, year = 1998, pages = {416--427}, publisher = {Morgan Kaufmann}, note = {The annual GP conference is now part of the {GECCO} conference}, documenturl = {http://www.cs.mun.ca/~tinayu/index_files/addr/public_html/pgp.new.pdf}, keywords = {PolyGP; enumerative ip; gp; higher-order functions; induction; inductive programming; program evolution; program synthesis}, annote = {A genetic programming system in Haskell using higher-order functions in order to evolve implicitly recursive programs} }
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Tina Yu and Chris Clack.
Recursion, lambda-abstractions and genetic programming.
In Riccardo Poli, W. B. Langdon, Marc Schoenauer, Terry Fogarty, and
Wolfgang Banzhaf, editors, EuroGP'98: Late Breaking Papers on the
First European Workshop on Genetic Programming (Paris, France, April14-15,
1998, pages 26-30, 1998.
@inproceedings{yu/clack:1998b, author = {Tina Yu and Chris Clack}, title = {Recursion, Lambda-Abstractions and Genetic Programming}, editor = {Riccardo Poli and W. B. Langdon and Marc Schoenauer and Terry Fogarty and Wolfgang Banzhaf}, booktitle = {{EuroGP'98}: Late Breaking Papers on the First European Workshop on Genetic Programming (Paris, France, April\,14--15, 1998}, year = 1998, pages = {26--30}, keywords = {enumerative ip; gp; higher-order functions; ifp; induction; inductive programming; program evolution; program synthesis} }
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Tina Yu.
An Analysis of the Impact of Functional Programming Techniques
on Genetic Programming.
PhD thesis, Department of Computer Science, University College
London, 1999.
@phdthesis{yu:1999, author = {Tina Yu}, title = {An Analysis of the Impact of Functional Programming Techniques on Genetic Programming}, school = {Department of Computer Science, University College London}, year = 1999, documenturl = {http://www.cs.mun.ca/~tinayu/index_files/addr/public_html/Thesis.pdf}, keywords = {enumerative ip; gp; higher-order functions; induction; inductive programming; program evolution; program synthesis} }
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Tina Yu.
Hierarchical processing for evolving recursive and modular programs
using higher-order functions and lambda abstraction.
Genetic Programming and Evolvable Machines, 2(4):345-380,
December 2001.
@article{yu:2001, author = {Tina Yu}, title = {Hierarchical Processing for Evolving Recursive and Modular Programs Using Higher-Order Functions and Lambda Abstraction}, journal = {Genetic Programming and Evolvable Machines}, year = 2001, volume = 2, number = 4, pages = {345--380}, month = {December}, publisher = {Springer Netherlands}, issn = {1389-2576 (Print) 1573-7632 (Online)}, url = {http://www.springerlink.com/content/h540822u22541721/}, doi = {10.1023/A:1012926821302}, keywords = {enumerative ip; gp; higher-order functions; ifp; induction; inductive programming; program evolution; program synthesis}, abstract = {We present a novel approach using higher-order functions and lambda abstraction to evolve recursive and modular programs. Moreover, a new term ``structure abstraction'' is introduced to describe the property emerged from the higher-order function program structure. We test this technique on the general even-parity problem. The results indicate that this approach is very effective with the general even-parity problem due to the appropriate selection of the foldr higher-order function. Initially, foldr structure abstraction identify the promising area of the search space at generation zero. Once the population is within the promising area, foldr structure abstraction provides hierarchical processing for search. Consequently, solutions to the general even-parity problem are found very efficiently. We identify the limitations of this new approach and conclude that only when the appropriate higher-order function is selected that the benefits of structure abstraction show.} }
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Tina Yu.
Polymorphism and genetic programming.
In Genetic Programming. 4th European Conference, EuroGP'01,
Lake Como, Italy, April18-20, 2001. Proceedings, volume 2038 of
Lecture Notes in Computer Science, pages 218-233, Berlin/Heidelberg,
2001. Springer.
@inproceedings{yu:2001b, author = {Tina Yu}, title = {Polymorphism and genetic programming}, booktitle = {Genetic Programming. 4th European Conference, {EuroGP'01}, Lake Como, Italy, April\,18--20, 2001. Proceedings}, year = 2001, series = {Lecture Notes in Computer Science}, volume = 2038, pages = {218--233}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-41899-3}, url = {http://www.springerlink.com/content/vx2bh2pt677k6bm0/}, abstract = {Types have been introduced to Genetic Programming (GP) by researchers with different motivation. We present the concept of types in GP and introduce a typed GP system, PolyGP, that supports polymorphism through the use of three different kinds of type variable. We demonstrate the usefulness of this kind of polymorphism in GP by evolving two polymorphic programs (nth and map) using the system. Based on the analysis of a series of experimental results, we conclude that this implementation of polymorphism is effective in assisting GP evolutionary search to generate these two programs. PolyGP may enhance the applicability of GP to a new class of problems that are difficult for other polymorphic GP systems to solve.}, doi = {10.1007/3-540-45355-5_17} }
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Tina Yu.
A higher-order function approach to evolve recursive programs.
In Tina Yu, Rick L. Riolo, and Bill Worzel, editors, Genetic
Programming Theory and Practice III, volume 9 of Genetic
Programming, chapter 7, pages 93-108. Springer, Ann Arbor, US, 12-14 May
2006.
@incollection{yu:2006, author = {Tina Yu}, title = {A Higher-Order Function Approach to Evolve Recursive Programs}, editor = {Tina Yu and Rick L. Riolo and Bill Worzel}, booktitle = {Genetic Programming Theory and Practice {III}}, publisher = {Springer}, year = 2006, volume = 9, series = {Genetic Programming}, chapter = 7, pages = {93--108}, address = {Ann Arbor, US}, month = {12-14 May}, issn = {1566-7863}, isbn = {978-0-387-28110-0 (Print) 978-0-387-28111-7 (Online)}, url = {http://www.springerlink.com/content/wh6jm67xpm1m1135/}, doi = {10.1007/0-387-28111-8_7}, abstract = {We demonstrate a functional style recursion implementation to evolve recursive programs. This approach re-expresses a recursive program using a non-recursive application of a higher-order function. It divides a program recursion pattern into two parts: the recursion code and the application of the code. With the higher-order functions handling recursion code application, GP effort becomes focused on the generation of recursion code. We employed this method to evolve two recursive programs: strstr C library function and programs that produce the Fibonacci sequence. In both cases, the program space defined by higher-order functions are very easy for GP to find a solution. We have learned about higher-order function selection and fitness assignment through this study. The next step will be to test the approach on applications with open-ended solutions, such as evolutionary design.}, keywords = {genetic algorithms; genetic programming; recursion; Fibonacci sequence; strstr; PolyGP; type systems; higher-order functions; recursion patterns; filter; foldr; scanr; lambda abstraction; functional programming languages; Haskell} }
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Chengqi Zhang, Hans W. Guesgen, and Wai-Kiang Yeap, editors.
PRICAI'04: Trends in Artificial Intelligence. 8th Pacific Rim
International Conference on Artificial Intelligence, Auckland, New Zealand,
Aug.9-13, 2004. Proceedings, volume 3157 of Lecture Notes in
Computer Science, Berlin/Heidelberg, 2004. Springer.
@proceedings{zhang_ea:2004, title = {{PRICAI'04}: Trends in Artificial Intelligence. 8th Pacific Rim International Conference on Artificial Intelligence, Auckland, New Zealand, Aug.\,9--13, 2004. Proceedings}, year = 2004, editor = {Chengqi Zhang and Hans W. Guesgen and Wai-Kiang Yeap}, volume = 3157, series = {Lecture Notes in Computer Science}, address = {Berlin\,/\,Heidelberg}, publisher = {Springer}, issn = {0302-9743 (Print) 1611-3349 (Online)}, isbn = {978-3-540-22817-2}, url = {http://springerlink.metapress.com/content/d27yf8bc7a64/}, doi = {10.1007/b99563} }
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