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Learning of Fuzzy Formal Language

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2 Author(s)
Shinichi Tamura ; Department of Information and Computer Sciences, Faculty of Engineering Science, Osaka University, Toyonaka, Osaka, Japan. ; Kokichi Tanaka

A learning model of fuzzy formal language is proposed and discussed. We continue training the learning machine by giving sets of sentences sequentially. As a result of parsing of the given teaching sentences, the learning machine reinforces fuzzy grades of membership of productions in an inherent fuzzy grammar of the machine. The convergence of the proposed model is considered, and it is shown that the grades of membership of desired productions are intensified by choosing an adequate teaching sequence of the sentence set. Furthermore, a concept of ``strongly equivalent,'' in which two grammars are not distinguished by any teaching sequence, is introduced.

Published in:

IEEE Transactions on Systems, Man, and Cybernetics  (Volume:SMC-3 ,  Issue: 1 )