Towards Understanding the Effects of Locality in GP

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

@InProceedings{Galvan-Lopez:2009:MICAI,

• author = "Edgar Galvan-Lopez and Michael O'Neill and Anthony Brabazon",
• title = "Towards Understanding the Effects of Locality in GP",
• booktitle = "Eighth Mexican International Conference on Artificial Intelligence, MICAI 2009",
• year = "2009",
• month = "9-13 " # nov,
• editor = "Arturo {Hernandez Aguirre} and Raul Monroy and Carlos Alberto {Reyes Garcia}",
• pages = "9--14",
• address = "Guanajuato, Mexico",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/MICAI.2009.17",
• isbn13 = "978-0-7695-3933-1",
• abstract = "Locality - how well neighbouring genotypes correspond to neighbouring phenotypes - has been defined as a key element in Evolutionary Computation systems to explore and exploit the search space. Locality has been studied empirically using the typical Genetic Algorithms (GAs) representation (i.e., bitstrings),and it has been argued that locality plays an important role in the performance of evolution. To our knowledge, there are no studies of locality using the typical Genetic Programming (GP)representation (i.e., tree-like structures). The aim of this paper is to shed some light on this matter by using GP. To do so, we use three different types of mutation taken from the specialised literature. We then perform extensive experiments by comparing the difference of distances at the genotype level between parent and offspring and their corresponding fitnesses. Our findings indicate that there is low-locality in GP when using these forms of mutation on a multimodal-deceptive landscape.",
• notes = "Also known as \cite{5372725}",

}

Genetic Programming entries for Edgar Galvan Lopez Michael O'Neill Anthony Brabazon

Citations