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, 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. weiterlesen