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Grammatical Inference as a Satisfiability Modulo Theories Problem (1705.10639v1)
Published 30 May 2017 in cs.FL, cs.LG, and cs.LO
Abstract: The problem of learning a minimal consistent model from a set of labeled sequences of symbols is addressed from a satisfiability modulo theories perspective. We present two encodings for deterministic finite automata and extend one of these for Moore and Mealy machines. Our experimental results show that these encodings improve upon the state-of-the-art, and are useful in practice for learning small models.