Abstract
Grammatical inference is the problem of learning a language from examples and counter-examples of words in this language. The common formulations of this problem make the fundamental hypothesis of the existence of a formal language underlying the data, to be discovered. Here we follow another approach, based on the following remarks. First of all, the initial hypothesis of a formal language to be identified does not hold for real data. Secondly, the algorithmic complexity of language identification is huge, even in the case of the simplest class of languages. Our approach aims at removing these two limitations. It allows the grammars produced to discriminate the sample words imperfectly, while it introduces the use of classic optimization techniques. Here we apply Tabu Search to the inference of regular grammars.
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References
D. Angluin. Queries and concept learning. Machine Learning, 2:319–342, 1988.
D. Angluin and C.H. Smith. Inductive inference: Theory and methods. Computing Surveys, 15(3):237–269, 1983.
C.M. Cook, A. Rosenfeld, and A.R. Aronson. Grammatical inference by hill-climbing. Information Sciences, 10:59–80, 1976.
P. Dupont. Regular grammatical inference from positive and negative samples by genetic search: the gig method. In Proceedings of the Second International Colloquim on Grammatical Inference, pages 236–245. Springer-Verlag, 1994.
F. Glover. Tabu search — part i. ORSA Journal on Computing, 1(3): 190–206, 1989.
F. Glover. Tabu search — part ii. ORSA Journal on Computing, 2(1):4–32, 1990.
E.M. Gold. Identification in the limit. Information and control, 10:447–474, 1967.
E. M. Gold. Complexity of automaton identification from given data. Information and Control, 37:302–320, 1978.
M. Li and P. Vitanyi. Inductive reasoning and kolmogorov complexity. In Proceedings of the 4th Annual IEEE Conference on Structure in Complexity Theory. IEEE Computer Society Press, June 1989.
J. Oncina and P. Garcia. Inferring regular languages in polynomial updated time. In Proceedings of the IVth Spanish Symposium on Pattern Recognition and Image Analysis, 1992.
J. Rissanen. Stochastic Complexity in Statistical Inquiry, volume 15 of Series in Computer Science. World Scientific, 1989.
R. J. Solomonoff. A formal theory of inductive inference. Information and Control, 7:1–22,224–254, 1964.
M. Tomita. Dynamic construction of finite-automata from examples using hill-climbing. In Proceedings of the 4th Annual Cognitive Science Conference, pages 105–108, 1982.
P. Wyard. Representational issues for context-free grammars induction using genetic algorithms. In Proceedings of the Second International Colloquim on Grammatical Inference, pages 222–235. Springer-Verlag, 1994.
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© 1996 Springer-Verlag Berlin Heidelberg
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Giordano, JY. (1996). Grammatical inference using Tabu Search. In: Miclet, L., de la Higuera, C. (eds) Grammatical Interference: Learning Syntax from Sentences. ICGI 1996. Lecture Notes in Computer Science, vol 1147. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0033363
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DOI: https://doi.org/10.1007/BFb0033363
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