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On the Effects of Outliers on Evolutionary Optimization

  • Dirk V. Arnold
  • Hans-Georg Beyer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2690)

Abstract

Most studies concerned with the effects of noise on evolutionary computation have assumed a Gaussian noise model. However, practical optimization strategies frequently face situations where the noise is not Gaussian, and sometimes it does not even have a finite variance. In particular, outliers may be present. In this paper, Cauchy distributed noise is used for modeling such situations. A performance law that describes how the progress of an evolution strategy using intermediate recombination scales in the presence of such noise is derived. Implications of that law are studied numerically, and comparisons with the case of Gaussian noise are drawn.

Keywords

Gaussian Noise Evolution Strategy Candidate Solution Noisy Environment Noise Strength 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Dirk V. Arnold
    • 1
  • Hans-Georg Beyer
    • 1
  1. 1.Department of Computer Science XIUniversity of DortmundDortmundGermany

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