Learning Automata and Grammars
نویسنده
چکیده
The problem of learning or inferring automata and grammars has been studied for decades and has connections to many disciplines, including bioinformatics, computational linguistics and pattern recognition. In this paper we present a short survey of basic models and techniques related to the grammatical inference and try to outline some new promising approaches which we expect to bring new light into this subject. For illustration, we introduce delimited stringrewriting systems as a sample model for grammatical inference and sketch the simplified version of the learning algorithm LARS for these systems.
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