Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language

Name: Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language
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Michael O'Neill · Conor Ryan

2012年12月 · Genetic Programming 第 4 冊 · Springer Science & Business Media

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Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language provides the first comprehensive introduction to Grammatical Evolution, a novel approach to Genetic Programming that adopts principles from molecular biology in a simple and useful manner, coupled with the use of grammars to specify legal structures in a search. Grammatical Evolution's rich modularity gives a unique flexibility, making it possible to use alternative search strategies - whether evolutionary, deterministic or some other approach - and to even radically change its behavior by merely changing the grammar supplied. This approach to Genetic Programming represents a powerful new weapon in the Machine Learning toolkit that can be applied to a diverse set of problem domains.
Beginning with an overview of the necessary background material in Genetic Programming and Molecular Biology, Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language outlines the current state of the art in grammatical and genotype-phenotype-based approaches. Following a description of Grammatical Evolution and its application to a number of example problems, an in-depth analysis of the approach is conducted, focusing on areas such as the degenerate genetic code, wrapping, and crossover. The book continues with a description of hot topics in Grammatical Evolution and presents possible directions for future research.