• DocumentCode
    2731490
  • Title

    On the analysis of self-adaptive recombination strategies: first results

  • Author

    Meyer-Nieberg, Silja ; Beyer, Hans-Georg

  • Author_Institution
    Dept. of Comput. Sci., Dortmund Univ., Germany
  • Volume
    3
  • fYear
    2005
  • fDate
    2-5 Sept. 2005
  • Firstpage
    2341
  • Abstract
    This paper presents first results on the analysis of self-adaptive (μ/μI, λ)-evolution strategies (ES). Applying a deterministic approach to model the evolution of the ES, equations describing the stationary state behavior of the normalized mutation strength and of the progress rate is derived. The analysis provides a deeper insight as to why the performance of the ES exhibits a sensitive dependence on the learning parameter τ.
  • Keywords
    evolutionary computation; function approximation; learning (artificial intelligence); probability; deterministic approach; evolution strategies; mutation strength; self-adaptive recombination; stationary state behavior; Computer science; Equations; Genetic mutations; Optimization methods; Performance analysis; Probability density function; Random variables; Scalability; Size control; Stationary state;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2005. The 2005 IEEE Congress on
  • Print_ISBN
    0-7803-9363-5
  • Type

    conf

  • DOI
    10.1109/CEC.2005.1554986
  • Filename
    1554986
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2731490