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Mutate large, but inherit small! On the analysis of rescaled mutations in (\(\tilde 1,\tilde \lambda\))-ES with noisy fitness data

  • Hans-Georg Beyer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1498)

Abstract

The paper presents the asymptotical analysis of a technique for improving the convergence of evolution strategies (ES) on noisy fitness data. This technique that may be called “Mutate large, but inherit small”, is discussed in light of the EPP (evolutionary progress principle). The derivation of the progress rate formula is sketched, its predictions are compared with experiments, and its limitations are shown. The dynamical behavior of the ES is investigated. It will be shown that standard self-adaptation has considerable problems to drive the ES in its optimum working regime. Remedies are provided to improve the self-adaptation.

Keywords

Progress Rate Loss Part Standard Normal Variate Parental Distance Evolution Strategy 
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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

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

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