Title
Coevolutionary Architectures with Straight Line Programs for Solving the Symbolic Regression Problem
Abstract
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.
Year
Venue
Keywords
2010
ICEC 2010: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON EVOLUTIONARY COMPUTATION
Genetic programming,Straight-line programs,Coevolution,Symbolic regression
Field
DocType
Citations 
Evolutionary algorithm,Expression (mathematics),Cooperative coevolution,Genetic programming,Evolution strategy,Tree structure,Artificial intelligence,Symbolic regression,Mathematics,Genetic program
Conference
0
PageRank 
References 
Authors
0.34
5
5