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The Theory of Evolution Strategies

  • Hans-Georg Beyer

Part of the Natural Computing Series book series (NCS)

Table of contents

  1. Front Matter
    Pages I-XIX
  2. Hans-Georg Beyer
    Pages 1-24
  3. Hans-Georg Beyer
    Pages 25-50
  4. Hans-Georg Beyer
    Pages 143-201
  5. Hans-Georg Beyer
    Pages 257-326
  6. Back Matter
    Pages 327-381

About this book

Introduction

Evolutionary Algorithms, in particular Evolution Strategies, Genetic Algorithms, or Evolutionary Programming, have found wide acceptance as robust optimization algorithms in the last ten years. Compared with the broad propagation and the resulting practical prosperity in different scientific fields, the theory has not progressed as much.
This monograph provides the framework and the first steps toward the theoretical analysis of Evolution Strategies (ES). The main emphasis is on understanding the functioning of these probabilistic optimization algorithms in real-valued search spaces by investigating the dynamical properties of some well-established ES algorithms. The book introduces the basic concepts of this analysis, such as progress rate, quality gain, and self-adaptation response, and describes how to calculate these quantities. Based on the analysis, functioning principles are derived, aiming at a qualitative understanding of why and how ES algorithms work.

Keywords

Evolution Strategy Evolutionary Algorithms Evolutionary Alorithm Theory Evolutionary Programming Evolutionsstrategie Evolutionäre Algorithmen Genetic Algorithms Genetische Algorithmen Optimization algorithms evolution evolutionary algorithm genetic algorithm

Authors and affiliations

  • Hans-Georg Beyer
    • 1
  1. 1.Department of Computer ScienceUniversity of DortmundDortmundGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-04378-3
  • Copyright Information Springer-Verlag Berlin Heidelberg 2001
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-08670-0
  • Online ISBN 978-3-662-04378-3
  • Series Print ISSN 1619-7127
  • Buy this book on publisher's site
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