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Beyond the GA: Extensions and Alternatives
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Author(s): Darryl Charles (University of Ulster, Ireland), Colin Fyfe (University of Paisley, UK), Daniel Livingstone (University of Paisley, UK)and Stephen McGlinchey (University of Paisley, UK)
Copyright: 2008
Pages: 18
Source title:
Biologically Inspired Artificial Intelligence for Computer Games
Source Author(s)/Editor(s): Darryl Charles (University of Ulster, Ireland), Colin Fyfe (University of Paisley, UK), Daniel Livingstone (University of Paisley, UK)and Stephen McGlinchey (University of Paisley, UK)
DOI: 10.4018/978-1-59140-646-4.ch008
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Abstract
The last two chapters introduced the standard GA, presented an example case study and explored some of the potential pitfalls in using evolutionary methods. This chapter focuses on a number of extensions and variations of the standard GA. While there is not room to cover them all, many extensions to GAs have been proposed usually in response to situations in which the simple GA does not perform particularly well.
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