Paper:
Language: English:
Fuzzy Adaptive Search Method for Genetic Programming
Yoichiro Maeda
Faculty of Information Science and Technology, Osaka Electro-Communication University 18-8, Hatsu-cho, Neyagawa, Osaka 572-8530, Japan
Received: June 11, 1998
Accepted: November 8, 1998
Keywords: Genetic programming, Adaptive search, Fuzzy rules, Mutation rate, Crossover rate
Journal ref: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.3, No.2 pp. 131-135, 1999
Abstract
The greatest problem of genetic programming (GP) is the large amount of calculation. We propose two methods for an efficient GP search - RPGP reducing void searches by pruning redundant nodes in GP and FASGP enabling proper search by tuning a mutation and crossover rate by fuzzy rules. Simulation proved the effectiveness of our proposal.
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