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Knowledge-based neurocomputing: a fuzzy logic approach. (English) Zbl 1166.68037

Studies in Fuzziness and Soft Computing 234. Berlin: Springer (ISBN 978-3-540-88076-9/hbk; 978-3-540-88077-6/ebook). xv, 100 p. (2009).
This book is part of the series “Studies in Fuzziness and Soft Computing”. It introduces a novel approach to building fuzzy rule-bases, called Fuzzy All-permutations Rule-Bases (FARB). The book starts with a broad introduction to the field of connectionism, namely artificial neural networks, fuzzy rule-bases, and neurocomputing, before it introduces the FARB concept. The authors show that inferring the FARB using standard tools from fuzzy logic theory yields an input-output relation that is mathematically equivalent to that of standard neural networks. Chapter 2 formally defines the FARB approach and shows that its special structure implies a closed-form formula for its input-output mapping.
Some special cases of the FARB are discussed in Chapter 3, where mathematical equivalence between these cases and various types of artificial neural networks is discussed. Example applications are presented to illustrate the main ideas. Since FARB may include either a large number of rules or complicated rules which may obstruct its comprehensibility, Chapter 4 presents a systematic procedure for rule reduction and simplification to minimize the effect of this. Application of FARB to large-scale problems is discussed in Chapters 5 and 6, where FARB is used for knowledge extraction from artificial neural networks trained to solve several benchmark problems. New knowledge-based design methods are described and their usefulness is demonstrated by designing networks to solve language recognition problems. Future research is summarized in Chapter 7, where potential applications based on transferring concepts and ideas between fuzzy logic and networks are discussed.

MSC:

68T05 Learning and adaptive systems in artificial intelligence
03B52 Fuzzy logic; logic of vagueness
68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
68T27 Logic in artificial intelligence
68T30 Knowledge representation
68T35 Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence
68-02 Research exposition (monographs, survey articles) pertaining to computer science
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