This book integrates fuzzy rule-languages with genetic algorithms, genetic programming, and classifier systems with the goal of obtaining fuzzy rule-based expert systems with learning capabilities. The main topics are first introduced by solving small problems, then a prototype implementation of the algorithm is explained, and last but not least the theoretical foundations are given. The second edition takes into account the rapid progress in the application of fuzzy genetic algorithms with a survey of recent developments in the field. The chapter on genetic programming has been revised. An exact uniform initialization algorithm replaces the heuristic presented in the first edition. A new method of abstraction, compound derivations, is introduced.
This work presents fuzzy rule-languages as links between quantitative and qualitative models. In the first part, the semantic of fuzzy rule-languages is extended with a type system and an object-oriented system. In the second part, fuzzy rule-languages are integrated with genetic algorithms and with classifier systems. For this purpose, the class of genetic algorithms over context-free languages has been developed.
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