Coevolutionary architectures with straight line programs for solving the symbolic regression problem

Autor: Borges Hernández, Cruz Enrique, Alonso González, César Luis, Montaña Arnaiz, José Luis, Cruz Echeandia, Marina de la, Ortega de la Puente, Alfonso
Přispěvatelé: UAM. Departamento de Ingeniería Informática, Herramientas Interactivas Avanzadas (ING EPS-003), Universidad de Cantabria
Jazyk: angličtina
Rok vydání: 2010
Předmět:
Zdroj: Biblos-e Archivo. Repositorio Institucional de la UAM
instname
ICEC 2010 : International Conference on Evolutionary Computation : proceedings : Valencia, Spain, 24-26 October 2010, Setúbal, SciTePress, 2010
ISSN: 2007-6746
DOI: 10.5220/0003075100410050
Popis: This is an electronic version of the paper presented at the International Conference on Evolutionary Computation (ICEC), held in Valencia (Spain) on 2010
To successfully apply evolutionary algorithms to the solution of increasingly complex problems we must develop effective techniques for evolving solutions in the form of interacting coadapted subcomponents. In this paper we present an architecture which involves cooperative coevolution of two subcomponents: a genetic program and an evolution strategy. As main difference with work previously done, our genetic program evolves straight line programs representing functional expressions, instead of tree structures. The evolution strategy searches for good values for the numerical terminal symbols used by those expressions. Experimentation has been performed over symbolic regression problem instances and the obtained results have been compared with those obtained by means of Genetic Programming strategies without coevolution. The results show that our coevolutionary architecture with straight line programs is capable to obtain better quality individuals than traditional genetic programming using the same amount of computational effort.
This work is partially supported by spanish grants TIN2007-67466-C02-02, MTM2004-01167 and S2009/TIC-1650
Databáze: OpenAIRE
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