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

  • Dave Cliff
  • Geoffrey F. Miller
2. Origins of Life and Evolution

DOI: 10.1007/3-540-59496-5_300

Part of the Lecture Notes in Computer Science book series (LNCS, volume 929)
Cite this paper as:
Cliff D., Miller G.F. (1995) Tracking the red queen: Measurements of adaptive progress in co-evolutionary simulations. In: Morán F., Moreno A., Merelo J.J., Chacón P. (eds) Advances in Artificial Life. ECAL 1995. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence), vol 929. Springer, Berlin, Heidelberg

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.

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Copyright information

© D. Cliff and G. F. Miller 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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