IEEE Transactions on Pattern Analysis and Machine Intelligence
Random DFA's can be approximately learned from sparse uniform examples
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Inference of Reversible Languages
Journal of the ACM (JACM)
Automata, Languages, and Machines
Automata, Languages, and Machines
Introduction To Automata Theory, Languages, And Computation
Introduction To Automata Theory, Languages, And Computation
Varieties Of Formal Languages
How Considering Incompatible State Mergings May Reduce the DFA Induction Search Tree
ICGI '98 Proceedings of the 4th International Colloquium on Grammatical Inference
ICGI '98 Proceedings of the 4th International Colloquium on Grammatical Inference
A Stochastic Search Approach to Grammar Induction
ICGI '98 Proceedings of the 4th International Colloquium on Grammatical Inference
A Comparative Study of Two Algorithms for Automata Identification
ICGI '00 Proceedings of the 5th International Colloquium on Grammatical Inference: Algorithms and Applications
Learning Stochastic Regular Grammars by Means of a State Merging Method
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
Inducing Probabilistic Grammars by Bayesian Model Merging
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
Identification of DFA: data-dependent vs data-independent algorithms
ICG! '96 Proceedings of the 3rd International Colloquium on Grammatical Inference: Learning Syntax from Sentences
Using knowledge to improve N-gram language modelling through the MGGI methodology
ICG! '96 Proceedings of the 3rd International Colloquium on Grammatical Inference: Learning Syntax from Sentences
Learning k-piecewise testable languages from positive data
ICG! '96 Proceedings of the 3rd International Colloquium on Grammatical Inference: Learning Syntax from Sentences
Learning Commutative Regular Languages
ICGI '08 Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications
A bibliographical study of grammatical inference
Pattern Recognition
Inferring regular trace languages from positive and negative samples
ICGI'10 Proceedings of the 10th international colloquium conference on Grammatical inference: theoretical results and applications
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Many varieties of regular languages have characterizations in terms of forbidden-patterns of their accepting finite automata. The use of patterns while inferring languages belonging to those families through the RPNI-Lang algorithm help to avoid overgeneralization in the same way as negative samples do. The aim of this paper is to describe and prove the convergence of a modification of the RPNI-Lang algorithm that we call FCRPNI. Preliminary experiments done seem to show that the convergence when we use FCRPNI for some subfamilies of regular languages is achieved faster than when we use just the RPNI algorithm.