Understanding EA Dynamics via Population Fitness Distributions

  • Elena Popovici
  • Kenneth De Jong
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2724)


This paper introduces a new tool to be used in conjunction with existing ones for a more comprehensive understanding of the behavior of evolutionary algorithms. Several research groups including [1],[3],[4] have shown how deeper insights into EA behavior can be obtained by focusing on the changes to the entire population fitness distribution rather than just ”best-so-far” curves. But characterizing how repeated applications of selection and reproduction modify this distribution over time proved to be very difficult to achieve analytically and was done successfully for only a few very specialized EAs and/or very simple fitness landscapes.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Elena Popovici
    • 1
  • Kenneth De Jong
    • 1
  1. 1.Department of Computer ScienceGeorge Mason UniversityFairfax

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