论文信息 - Identification of automata by sequential learning

Identification of automata by sequential learning

Identification of automata from input/output sequences can be useful for the understanding of their functioning when differences appear between a theoretical behaviour and a real one. Two new inference algorithms are presented which are based on a sequential learning scheme: The different states are discovered through an induction-contradiction-discrimination procedure.

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