Self-Adaptive Heuristics for Evolutionary Computation: 147 (Studies in Computational Intelligence, 147) - Image 1

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Springer Self-Adaptive Heuristics for Evolutionary Computation: 147 (Studies in Computational Intelligence, 147)

Name: Self-Adaptive Heuristics for Evolutionary Computation: 147 (Studies in Computational Intelligence, 147)
Brand: Springer
Price: 50.53 GBP
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23895686

AI & Machine Learning

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Description

Evolutionary algorithms are successful biologically inspired meta-heuristics. Their success depends on adequate parameter settings. The question arises: how can evolutionary algorithms learn parameters automatically during the optimization? Evolution strategies gave an answer decades ago: self-adaptation. Their self-adaptive mutation control turned out to be exceptionally successful. But nevertheless self-adaptation has not achieved the attention it deserves. This book introduces various types of self-adaptive parameters for evolutionary computation. Biased mutation for evolution strategies is useful for constrained search spaces. Self-adaptive inversion mutation accelerates the search on combinatorial TSP-like problems. After the analysis of self-adaptive crossover operators the book concentrates on premature convergence of self-adaptive mutation control at the constraint boundary. Besides extensive experiments, statistical tests and some theoretical investigations enrich the analysis of the proposed concepts.

Product Specifications

Brand: Springer
Model: 23895686
Format: hardcover
ASIN: 3540692800
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 19 August 2008
Listed Since: 20 May 2008

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Springer Self-Adaptive Heuristics for Evolutionary Computation: 147 (Studies in Computational Intelligence, 147)

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