Investigating Mapping Order in piGE

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{fagan_etal:cec2010,

• author = "David Fagan and Miguel Nicolau and Michael O'Neill and Edgar Galvan-Lopez and Anthony Brabazon and Sean McGarraghy",
• title = "Investigating Mapping Order in {piGE}",
• booktitle = "2010 IEEE World Congress on Computational Intelligence",
• pages = "3058--3064",
• year = "2010",
• address = "Barcelona, Spain",
• month = "18-23 " # jul,
• organization = "IEEE Computational Intelligence Society",
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming, grammatical evolution",
• isbn13 = "978-1-4244-6910-9",
• DOI = "doi:10.1109/CEC.2010.5586204",
• size = "7 pages",
• abstract = "We present an investigation into the genotype-phenotype map in Position Independent Grammatical Evolution (piGE). Previous studies have shown piGE to exhibit a performance increase over standard GE. The only difference between the two approaches is in how the genotype-phenotype mapping process is performed. GE uses a leftmost non terminal expansion, while piGE evolves the order of mapping as well as the content. In this study, we use the idea of focused search to examine which aspect of the piGE mapping process provides the lift in performance over standard GE by applying our approaches to four benchmark problems taken from specialised literature. We examined the traditional piGE approach and compared it to two setups which examined the extremes of mapping order search and content search, and against setups with varying ratios of content and order search. In all of these tests a purely content focused piGE was shown to exhibit a performance gain over the other setups.",
• notes = "WCCI 2010. Also known as \cite{5586204}",

}

Genetic Programming entries for David Fagan Miguel Nicolau Michael O'Neill Edgar Galvan Lopez Anthony Brabazon Sean McGarraghy

Citations