Learning approximately regular languages with reversible languages
Theoretical Computer Science
Learning Local Languages and Their Application to DNA Sequence Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Splicing representations of strictly locally testable languages
Discrete Applied Mathematics
Inference of Reversible Languages
Journal of the ACM (JACM)
Counter-Free Automata (M.I.T. research monograph no. 65)
Counter-Free Automata (M.I.T. research monograph no. 65)
Some Classes of Regular Languages Identifiable in the Limit from Positive Data
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
Learnability of automatic classes
LATA'10 Proceedings of the 4th international conference on Language and Automata Theory and Applications
Learnability of automatic classes
Journal of Computer and System Sciences
Automatic learning of subclasses of pattern languages
Information and Computation
Automatic learners with feedback queries
Journal of Computer and System Sciences
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In algorithmic learning theory fundamental roles are played by the family of languages that are locally testable in the strict sense and by the family of reversible languages. These two families are shown to be the first two members of an infinite sequence of families of regular languages the members of which are learnable in the limit from positive data only. A uniform procedure is given for deciding, for each regular language R and each of our specified families, whether R belongs to the family. The approximation of arbitrary regular languages by languages belonging to these families is discussed. Further, we will give a uniform scheme for learning these families from positive data. Several research problems are also suggested.