Automatic Programming in an Arbitrary Language: Evolving Programs with Grammatical Evolution

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

@PhdThesis{oneill:thesis,

• author = "Michael O'Neill",
• title = "Automatic Programming in an Arbitrary Language: Evolving Programs with Grammatical Evolution",
• school = "University Of Limerick",
• year = "2001",
• address = "Ireland",
• month = aug,
• email = "michael.oneill@ul.ie",
• keywords = "genetic algorithms, genetic programming, grammatical evolution",
• URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/oneill/MichaelONeillThesis.ps.gz",
• size = "163 pages",
• abstract = "We present a novel Evolutionary Automatic Programming system, Grammatical Evolution that is capable of generating programs in an arbitrary language from a binary string. Grammatical Evolution adopts a genotype to phenotype mapping; the genotype is the raw genetic material, analogous to the DNA of Molecular Biology, and the phenotype the functional program that is generated (the equivalent of proteins in Molecular Biology). Resulting from the genotype-phenotype distinction, and inspired by Molecular Biology, a number of features are introduced that result in benefits for Grammatical Evolution. We demonstrate Grammatical Evolution's viability on a number of proof of concept problems with performance on a par with, and in some cases superior to Genetic Programming. An analysis of the system is conducted in which we focus on a number of features arising directly from the genotype-phenotype distinction, namely the degenerate genetic code, and the novel, wrapping operator. We conclude the investigations with an analysis of the effects of the genetic operator of crossover on Grammatical Evolution, before detailing our conclusions and outlining directions for future research.",

}

Genetic Programming entries for Michael O'Neill

Citations