Learning regular languages using RFSAs

Learning regular languages using RFSAs

Residual languages are important and natural components of regular languages and several grammatical inference algorithms naturally rely on this notion. In order to identify a given target language L, classical inference algorithms try to identify words which de/ne identical residual languages of L. Here, we study whether it could be interesting to perform a tighter analysis by identifying incl...

Learning Regular Languages using RFSAs ?

Learning Regular Languages Using RFSA

Learning Regular Languages Using Nondeterministic Finite Automata

A new general method for inference of regular languages using nondeterministic automata as output has recently been developed and proved to converge. The aim of this paper is to describe and analyze the behavior of two implementations of that method and to compare it with two well known algorithms for the same task. A complete set of experiments has been carried out and the results of the new a...

Learning Regular Omega Languages

We provide an algorithm for learning an unknown regular set of infinite words, using membership and equivalence queries. Three variations of the algorithm learn three different canonical representations of omega regular languages, using the notion of families of dfas. One is of size similar to L$, a dfa representation recently learned using L ∗ [7]. The second is based on the syntactic forc, in...