Adaptive Representations for Improving Evolvability, Parameter Control, and Parallelization of Gene Expression Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@Article{Browne:2010:ACISC,

• author = "Nigel P. A. Browne and Marcus V. {dos Santos}",
• title = "Adaptive Representations for Improving Evolvability, Parameter Control, and Parallelization of Gene Expression Programming",
• journal = "Applied Computational Intelligence and Soft Computing",
• year = "2010",
• volume = "2010",
• pages = "Article ID 409045",
• keywords = "genetic algorithms, genetic programming, gene expression programming",
• URL = "http://downloads.hindawi.com/journals/acisc/2010/409045.pdf",
• DOI = "doi:10.1155/2010/409045",
• size = "19 pages",
• abstract = "Gene Expression Programming (GEP) is a genetic algorithm that evolves linear chromosomes encoding nonlinear (tree-like) structures. In the original GEP algorithm, the genome size is problem specific and is determined through trial and error. In this work, a method for adaptive control of the genome size is presented. The approach introduces mutation, transposition, and recombination operators that enable a population of heterogeneously structured chromosomes, something the original GEP algorithm does not support. This permits crossbreeding between normally incompatible individuals, speciation within a population, increases the evolvability of the representations, and enhances parallel GEP. To test our approach, an assortment of problems were used, including symbolic regression, classification, and parameter optimization. Our experimental results show that our approach provides a solution for the problem of self-adaptive control of the genome size of GEP's representation.",

}

Genetic Programming entries for Nigel P A Browne Marcus Vinicius dos Santos

Citations