Abstract
A new type of generalised fuzzy rules and generalised fuzzy production systems and a corresponding reasoning method are developed. They are implemented in a connectionist architecture and called connectionist fuzzy production systems. They combine all the features of the symbolic AI production systems, the fuzzy production systems and the connectionist systems. A connectionist method for learning generalised fuzzy productions from raw data is also presented. The main conclusion reached is that connectionist fuzzy production systems are very powerful as fuzzy reasoning machines and they may well inspire new methods of plausible representation of inexact knowledge and new inference techniques for approximate reasoning.
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© 1994 Springer-Verlag Berlin Heidelberg
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Kasabov, N.K. (1994). Connectionist fuzzy production systems. In: Ralescu, A.L. (eds) Fuzzy Logic in Artificial Intelligence. FLAI 1993. Lecture Notes in Computer Science, vol 847. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58409-9_9
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DOI: https://doi.org/10.1007/3-540-58409-9_9
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