Fuzzy Logic, Neural Networks, and Evolutionary Computation [electronic resource] : IEEE/Nagoya-University World Wisepersons Workshop Nagoya, Japan, November 14–15, 1995 Selected Papers / edited by Takeshi Furuhashi, Yoshiki Uchikawa.

The design of hybrid fuzzy/evolutionary multiobjective optimization algorithms -- Structure identification of acquired knowledge in fuzzy inference by genetic algorithms -- A fuzzy classifier system that generates linguistic rules for pattern classification problems -- Numerical coding and unfair average crossover in GA for fuzzy rule extraction in dynamic environments -- Acquisition of fuzzy rules from DNA coding method -- Experimental study on acquisition of optimal action for autonomous mobile robot to avoid moving multiobstacles -- New approaches on structure identification of fuzzy models: Case study in an electro-mechanical system -- A generic fuzzy neuron and its application to motion estimation -- Fizzy-Fuzzy inferencing -- Multi-layer perceptron design using Delaunay triangulations -- A genetic algorithm for planning coal purchase of a real electric power plant -- “CAM-Brain? ATR's billion neuron artificial brain project a three year progress report.

This book includes a selection of twelve carefully revised papers chosen from the papers accepted for presentation at the 4th IEEE/Nagoya-University World Wisepersons Workshop held in Nagoya in November 1995. The combining of the technologies of fuzzy logic, neural networks, and evolutionary computation is expected to open up a new paradigm of machine learning for the realization of human-like information generating systems. The excellent papers presented are organized in sections on fuzzy and evolutionary computation, fuzzy and learning automata, fuzzy and neural networks, genetic algorithms, and CAM-brain.