Titlebook: Topics in Grammatical Inference; Jeffrey Heinz,José M. Sempere Book 2016 Springer-Verlag Berlin Heidelberg 2016 Automata Theory.Formal Lan

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On the Inference of Finite State Automata from Positive and Negative Data, drawback of their results is that they may obtain hypotheses that may be inconsistent with the provided data. This drawback was solved by the . and Lang algorithms. Aside from these works, other works have introduced more efficient algorithms with respect to the training data. The direct consequenc

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Efficiency in the Identification in the Limit Learning Paradigm,best incorporate a notion of efficiency and tractability into this framework. This chapter surveys the different refinements that have been developed and studied, and the challenges they face. Main results for each formalization, along with comparisons, are provided.

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Learning Grammars and Automata with Queries,elds, is formalised in a setting called active learning or query learning. By controlling better the information to which one has access, this setting provides us with a better understanding of the hardness of learning tasks. But the setting also allows us to solve practical learning situations, for which new algorithms are needed.