Cooperative coevolution has proven to be a promising technique for solving complex combinatorial optimization problems. In this paper, we present four different strategies which involve cooperative coevolution of a genetic program and of a population of constants evolved by a genetic algorithm. The genetic program evolves expressions that solve a problem, while the genetic algorithm provides “good” values for the numeric terminal symbols used by those expressions. Experiments have been performed on three symbolic regression problems and on a “real-world” biomedical application. Results are encouraging and confirm that our coevolutionary algorithms can be used effectively in different domains

Vanneschi, L., Mauri, G., Valsecchi, A., Cagnoni, S. (2006). Heterogeneous cooperative coevolution: Strategies of integration between GP and GA. In Proceedings of the 8th annual conference on Genetic and evolutionary computation, Gecco 2006 (pp.361-368). New York : ACM Press [10.1145/1143997.1144062].

Heterogeneous cooperative coevolution: Strategies of integration between GP and GA

VANNESCHI, LEONARDO;MAURI, GIANCARLO;
2006

Abstract

Cooperative coevolution has proven to be a promising technique for solving complex combinatorial optimization problems. In this paper, we present four different strategies which involve cooperative coevolution of a genetic program and of a population of constants evolved by a genetic algorithm. The genetic program evolves expressions that solve a problem, while the genetic algorithm provides “good” values for the numeric terminal symbols used by those expressions. Experiments have been performed on three symbolic regression problems and on a “real-world” biomedical application. Results are encouraging and confirm that our coevolutionary algorithms can be used effectively in different domains
slide + paper
genetic algorithms; genetic programming; coevolution; combinatorial optimization
English
Genetic and Evolutionary Computation Conference
2006
Proceedings of the 8th annual conference on Genetic and evolutionary computation, Gecco 2006
1595931864
2006
361
368
none
Vanneschi, L., Mauri, G., Valsecchi, A., Cagnoni, S. (2006). Heterogeneous cooperative coevolution: Strategies of integration between GP and GA. In Proceedings of the 8th annual conference on Genetic and evolutionary computation, Gecco 2006 (pp.361-368). New York : ACM Press [10.1145/1143997.1144062].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/16493
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