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Self-adaptation on the Ridge Function Class: First Results for the Sharp Ridge

  • Hans-Georg Beyer
  • Silja Meyer-Nieberg
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4193)

Abstract

This paper presents first results of an analysis of the σ-self-adaptation mechanism on the sharp ridge for non-recombinative (1,λ) evolution strategies (ES). To analyze the ES’s evolution, we consider the so-called evolution equations which describe the one-generation change. Neglecting stochastic perturbations and considering only the mean value dynamics, we will investigate possible causes why self-adaptation can fail on the sharp ridge.

Keywords

Taylor Series Evolution Strategy Sphere Model Progress Rate Learning Parameter 
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 2006

Authors and Affiliations

  • Hans-Georg Beyer
    • 1
  • Silja Meyer-Nieberg
    • 2
  1. 1.Department of Computer ScienceVorarlberg University of Applied SciencesDornbirnAustria
  2. 2.Department of Computer ScienceUniversität der Bundeswehr MünchenNeubibergGermany

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