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Adaptive Genetic Algorithms Based on Coevolution with Fuzzy Behaviors (1998)
| Venue: | DEPT. OF COMPUTER SCIENCE AND A. I., UNIVERSITY OF GRANADA, SPAIN. (AVAILABLE |
| Citations: | 2 - 1 self |
BibTeX
@TECHREPORT{Herrera98adaptivegenetic,
author = {F. Herrera and M. Lozano},
title = {Adaptive Genetic Algorithms Based on Coevolution with Fuzzy Behaviors},
institution = {DEPT. OF COMPUTER SCIENCE AND A. I., UNIVERSITY OF GRANADA, SPAIN. (AVAILABLE},
year = {1998}
}
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Abstract
Adaptive genetic algorithms dynamically adjust the genetic algorithm configuration during the course of evolving a problem solution in order to offer an appropriate balance between exploration (overall search in the solution space) and exploitation (localized search in the promising regions discovered in that space). One promising way followed for building adaptive genetic algorithms involves the application of fuzzy logic controllers for tuning genetic algorithm control parameters. In this paper, a general model based on fuzzy logic controllers is presented for adapting parameters that control the application of any genetic operator. Our proposal is called coevolution with fuzzy behaviors. A fuzzy behavior is a vector with the linguistic values of the fuzzy rule consequent of a fuzzy logic controller, that encodes its fuzzy rule base. Control parameter values are computed for each set of parents that undergo the genetic operator, using a fuzzy logic controller that considers particula...
Keyphrases
fuzzy behavior adaptive genetic algorithm fuzzy logic controller genetic operator genetic algorithm configuration control parameter value linguistic value problem solution overall search promising region solution space appropriate balance fuzzy rule base general model fuzzy rule consequent genetic algorithm control parameter
