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A New Approach for Predicting the Final Outcome of Evolution Strategy Optimization Under Noise

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Abstract

Differential-geometric methods are applied to derive steady state conditions for the (μ/μ I ,λ)-ES on the general quadratic test function disturbed by fitness noise of constant strength. A new approach for estimating the expected final fitness deviation observed under such conditions is presented. The theoretical results obtained are compared with real ES runs, showing a surprisingly excellent agreement.

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Authors and Affiliations

  1. Department of Computer Science XI, University of Dortmund, D-44221, Dortmund, Germany

    Hans-George Beyer & Silja Meyer-Nieberg

  2. Faculty of Computer Science, Dalhousie University, B3H 1W5, Halifax, NS, Canada

    Dirk V. Arnold

Authors
  1. Hans-George Beyer
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  2. Dirk V. Arnold
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  3. Silja Meyer-Nieberg
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Correspondence to Hans-George Beyer.

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Beyer, HG., Arnold, D.V. & Meyer-Nieberg, S. A New Approach for Predicting the Final Outcome of Evolution Strategy Optimization Under Noise. Genet Program Evolvable Mach 6, 7–24 (2005). https://doi.org/10.1007/s10710-005-7617-y

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  • DOI: https://doi.org/10.1007/s10710-005-7617-y

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