Yasuki Kakishita

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We propose an efficient automata-based approach to extract behavioral units and rules from continuous sequential data of animal behavior. By introducing novel extensions, we integrate two elemental methods—the N-gram model and Angluin’s machine learning algorithm into an ethological data mining framework. This allows us to obtain the minimized(More)
We propose a new automata-based approach to modeling birdsongs on the basis of Angluin's induction algorithm, which ensures that k-reversible languages can be learned from positive samples with polynomial time. There are similarities between Angluin's algorithm and the vocal learning of songbirds; for example, during a critical period, songbirds also learn(More)
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