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Genetic and Evolutionary Computation Conference

GECCO 2003: Genetic and Evolutionary Computation — GECCO 2003 pp 1604–1605Cite as

Understanding EA Dynamics via Population Fitness Distributions

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2724))

Abstract

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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References

  1. Lee Altenberg. The Schema Theorem and Price’s Theorem. In L. Darrell Whitley and Michael D. Vose, editors, Foundations of Genetic Algorithms 3, pages 23–49, Estes Park, Colorado, USA, 1995. Morgan Kaufmann.

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  2. R. Jain. The Art of Computer Systems Performance Analysis. John Wiley and Sons, Inc., New York, 1991.

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  3. H. Mühlenbein and D. Schlierkamp-Voosen. Predictive models for the breeder genetic algorithm. Evolutionary Computation, 1(1):25–49, 1993.

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  4. J. Shapiro, A. Prügel-Bennett, and M. Rattray. A statistical mechanical formulation of the dynamics of genetic algorithms. In Terence C. Fogarty, editor, Evolutionary Computing, AISB Workshop, volume 993 of Lecture Notes in Computer Science. Springer, 1994.

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Author information

Authors and Affiliations

  1. Department of Computer Science, George Mason University, Fairfax, VA, 22030

    Elena Popovici & Kenneth De Jong

Authors
  1. Elena Popovici
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  2. Kenneth De Jong
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Editor information

Editors and Affiliations

  1. Center for Applied Scientific Computing (CASC), Lawrence Livermore National Laboratory, 7000 East Avenue, L-561, Livermore, CA, 94550, USA

    Erick Cantú-Paz

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© 2003 Springer-Verlag Berlin Heidelberg

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Cite this paper

Popovici, E., De Jong, K. (2003). Understanding EA Dynamics via Population Fitness Distributions. In: Cantú-Paz, E., et al. Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2724. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45110-2_46

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  • DOI: https://doi.org/10.1007/3-540-45110-2_46

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40603-7

  • Online ISBN: 978-3-540-45110-5

  • eBook Packages: Springer Book Archive

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