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Polynomial time inference of a subclass of context-free transformations

Authors:

Hiroki Arimura,

Hiroki Ishizaka,

Takeshi ShinoharaAuthors Info & Claims

COLT '92: Proceedings of the fifth annual workshop on Computational learning theory

Pages 136 - 143

https://doi.org/10.1145/130385.130400

Published: 01 July 1992 Publication History

Abstract

This paper deals with a class of Prolog programs, called context-free term transformations (CTF). We present a polynomial time algorithm to identify a subclass of CFT, whose program consists of at most two clauses, from positive data; The algorithm uses 2-mmg (2-minimal multiple generalization) algorithm, which is natural extension of Plotkin's least generalization algorithm, to reconstruct the pair of heads of the unknown program. Using this algorithm, we show the consistent and conservative polynomial time identifiability of the class of tree languages defined by CFTFB_uniq together with tree languages defined by pairs of two tree patterns, both of which are proper subclasses of CFT, in the limit from positive data.

References

[1]

D. Angluin. Finding common patterns to a set of strings. In Proceedings of the 11th Annual Symposium on Theory of Computing, pp. 130-141, 1979.

Digital Library

[2]

D. Angluin. Inference of reversible languages. Journal of the ACM, Vol. 29, pp. 741-765, 1982.

Digital Library

[3]

H. Arimura, T. Shinohara, and S. Otsuki. Polynomial time inference of unions of tree pattern languages. In Proceedings of the Second Workshop on Algorithmic Learning Theory, pp. 105-114, 1991.

[4]

H. Ishizaka. Model inference incorporating generalization. Journal of Information Processing, Vol. 11, No. 3, pp. 206-211, 1988.

Digital Library

[5]

J.W. Lloyd. Foundations of Logic Programming. Springer Verlag, second edition, 1987.

Digital Library

[6]

J-L. Lassez, M.J. Maher, and K. Marriott. Unification revisited. In J. Minker, editor, Foundations of Deductive Databases and Logic Programming, pp. 587-625. Morgan Kaufmann, 1988.

Digital Library

[7]

K. Marriott, L. Naish, and J-L. Lassez. Most specific logic programs. In Proc. 5th ICLP, pp. 909-923. MIT Press, 1988.

[8]

S. Muggleton. Machine invention of firstorder predicates by inverting resolution. In Proceedings of the Fifth International Conference on Machine Learning, pp. 339-352, 1988.

Digital Library

[9]

L. Pitt. Inductive inference, dfas, and computational complexity. In K. P. Jantke, editor, Proceedings of International Workshop on Analogical and Inductive Inference, 1989. Lecture Notes in Computer Science 397.

Digital Library

[10]

G. Plotkin. A note on inductive generalization. In B. Meltzer and D. Mitchie, editors, Machine Intelligence, volume 5, pp. 153-163. Edinburgh University Press, 1970.

[11]

Y. Sakakibara. An efficient learning of context-free grammars from positive structural examples. Technical report, FUJITSU LABORATORIES, IIAS, 1989. To be appeared in Information and Computation.

Digital Library

[12]

E.Y. Shapiro. Inductive inference of theories from facts. Technical Report 192, Yale University, Department of Computer Science, 1981.

[13]

T. Shinohara. Inductive inference of monotonic formal systems from positive data. In Proceedings of the First International Workshop on Algorithmic Learning Theory, pp. 339-351, 1990.

[14]

K. Wright. Identification of unions of languages drawn from an identifiable class. In Proceedings of the 2nd Annual Workshop on Computational Learning Theory, pp. 328- 333, 1989.

Digital Library

[15]

K. Wright. Inductive Inference of Pattern Languages. PhD thesis, University of Pittsburgh, 1989.

Digital Library

Cited By

Krishna Rao MSattar A(2007)Learning Logic Programs with Local Variables from Positive ExamplesAdvanced Topics in Artificial Intelligence10.1007/3-540-46695-9_41(469-471)Online publication date: 12-Aug-2007
https://doi.org/10.1007/3-540-46695-9_41
Ishizaka HArimura HShinohara T(2005)Efficient inductive inference of primitive Prologs from positive dataAlgorithmic Learning Theory10.1007/3-540-57369-0_34(135-146)Online publication date: 31-May-2005
https://doi.org/10.1007/3-540-57369-0_34
Shinohara TArimura H(2000)Inductive inference of unbounded unions of pattern languages from positive dataTheoretical Computer Science10.1016/S0304-3975(99)00270-4241:1-2(191-209)Online publication date: 28-Jun-2000
https://dl.acm.org/doi/10.1016/S0304-3975%2899%2900270-4
Show More Cited By

Index Terms

Polynomial time inference of a subclass of context-free transformations
1. Theory of computation
  1. Computational complexity and cryptography
    1. Complexity classes
  2. Logic
    1. Constraint and logic programming

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Published In

cover image ACM Conferences

COLT '92: Proceedings of the fifth annual workshop on Computational learning theory

July 1992

452 pages

ISBN:089791497X

DOI:10.1145/130385

Chairman:
David Haussler

Copyright © 1992 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

Publication History

Published: 01 July 1992

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COLT92

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COLT92: 5th Annual Workshop on Computational Learning Theory

July 27 - 29, 1992

Pennsylvania, Pittsburgh, USA

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Overall Acceptance Rate 35 of 71 submissions, 49%

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Cited By

Krishna Rao MSattar A(2007)Learning Logic Programs with Local Variables from Positive ExamplesAdvanced Topics in Artificial Intelligence10.1007/3-540-46695-9_41(469-471)Online publication date: 12-Aug-2007
https://doi.org/10.1007/3-540-46695-9_41
Ishizaka HArimura HShinohara T(2005)Efficient inductive inference of primitive Prologs from positive dataAlgorithmic Learning Theory10.1007/3-540-57369-0_34(135-146)Online publication date: 31-May-2005
https://doi.org/10.1007/3-540-57369-0_34
Shinohara TArimura H(2000)Inductive inference of unbounded unions of pattern languages from positive dataTheoretical Computer Science10.1016/S0304-3975(99)00270-4241:1-2(191-209)Online publication date: 28-Jun-2000
https://dl.acm.org/doi/10.1016/S0304-3975%2899%2900270-4
Cohen WPage C(1995)Polynomial learnability and Inductive Logic Programming: Methods and resultsNew Generation Computing10.1007/BF0303723113:3-4(369-409)Online publication date: Dec-1995
https://doi.org/10.1007/BF03037231
Frazier MPage C(1993)Learnability in inductive logic programmingProceedings of the eleventh national conference on Artificial intelligence10.5555/1867270.1867285(93-98)Online publication date: 11-Jul-1993
https://dl.acm.org/doi/10.5555/1867270.1867285

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