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Tracking the red queen: Measurements of adaptive progress in co-evolutionary simulations

  • Dave Cliff
  • Geoffrey F. Miller
2. Origins of Life and Evolution
Part of the Lecture Notes in Computer Science book series (LNCS, volume 929)

Abstract

Co-evolution can give rise to the “Red Queen effect”, where interacting populations alter each other's fitness landscapes. The Red Queen effect significantly complicates any measurement of co-evolutionary progress, introducing fitness ambiguities where improvements in performance of co-evolved individuals can appear as a decline or stasis in the usual measures of evolutionary progress. Unfortunately, no appropriate measures of fitness given the Red Queen effect have been developed in artificial life, theoretical biology, population dynamics, or evolutionary genetics. We propose a set of appropriate performance measures based on both genetic and behavioral data, and illustrate their use in a simulation of co-evolution between genetically specified continuous-time noisy recurrent neural networks which generate pursuit and evasion behaviors in autonomous agents.

Keywords

Autonomous Agent Fitness Landscape Artificial Life Fitness Score Evolutionary Progress 
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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References

  1. 1.
    M. Bedau and N. Packard. Measurement of evolutionary activity, teleology, and life. In C. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, eds, Artificial Life II, pp.431–461. Addison Wesley, 1992.Google Scholar
  2. 2.
    D. Cliff, I. Harvey, P. Husbands. Explorations in evolutionary robotics. Adapt. Behav., 2(1):71–108, 1993.Google Scholar
  3. 3.
    D. Cliff and G. F. Miller. Co-evolution of pursuit and evasion II: simulation methods and results. COGS Technical Report CSRP377, University of Sussex, 1995.Google Scholar
  4. 4.
    D. Cliff and G. F. Miller. Tracking the Red Queen: Measurements of coevolutionary progress in open-ended simulations. COGS Technical Report CSRP363, University of Sussex, 1995.Google Scholar
  5. 5.
    R. Dawkins. The Blind Watchmaker. Longman, Essex, 1986.Google Scholar
  6. 6.
    N. Eldredge. Macroevolutionary dynamics: Species, niches, and adaptive peaks. McGraw-Hill, 1989.Google Scholar
  7. 7.
    D. J. Futuyama and M. Slatkin, editors. Coevolution. Sinauer, 1983.Google Scholar
  8. 8.
    R. C. Gonzalez and P. Wintz. Digital Image Processing. Addison-Wesley, 1977.Google Scholar
  9. 9.
    S. J. Gould. Wonderful Life: The Burgess Shale and the Nature of History. Penguin, 1989.Google Scholar
  10. 10.
    S. Kauffman. The Origins of Order: Self-Organization and Selection in Evolution. OUP, 1993.Google Scholar
  11. 11.
    J. R. Krebs and N. B. Davies. An Introduction to Behaviuoral Ecology. Blackwell Scientific, 1993.Google Scholar
  12. 12.
    G. F. Miller and D. Cliff. Co-evolution of pursuit and evasion I: Biological and game-theoretic foundations. Technical Report CSRP311, University of Sussex School of Cognitive and Computing Sciences, 1994.Google Scholar
  13. 13.
    G. F. Miller and D. Cliff. Protean behavior in dynamic games: Arguments for the co-evolution of pursuit-evasion tactics. In D. Cliff, P. Husbands, J.-A. Meyer, and S. Wilson, editors, Proc. Third Int. Conf. Simulation Adaptive Behavior (SAB94), pages 411–420. M.I.T. Press Bradford Books, 1994.Google Scholar
  14. 14.
    E. Renshaw. Modelling Biological Populations in Space and Time. Cambridge University Press, 1991.Google Scholar
  15. 15.
    C. Reynolds. Competition, coevolution, and the game of tag. In R. Brooks and P. Maes, editors, Artificial Life IV, pages 59–69. M.I.T. Press Bradford Books, 1994.Google Scholar
  16. 16.
    M. Ridley. The Red Queen: Sex and the evolution of human nature. Viking, London, 1993.Google Scholar
  17. 17.
    J. Segers and W. D. Hamilton. Parasites and sex. In R. E. Michod and B. R. Levin, editors, The evolution of sex: some current, ideas, pages 176–193. Sinauer, Sunderland, MA, 1988.Google Scholar
  18. 18.
    K. Sims. Evolving 3D morphology and behavior by competition. In R. Brooks and P. Maes, editors, Artificial Life IV, pages 28–39. M.I.T. Press Bradford Books, 1994.Google Scholar
  19. 19.
    L. van Valen. A new evolutionary law. Evolutionary Theory, 1:1–30, 1973.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Dave Cliff
    • 1
  • Geoffrey F. Miller
    • 2
  1. 1.School of Cognitive and Computing SciencesUniversity of SussexBrightonUK
  2. 2.Department of PsychologyUniversity of NottinghamNottinghamUK

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