The N-Strikes-Out Algorithm: A Steady-State Algorithm for Coevolution

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "T. Miconi and A. Channon",
  title =        "The N-Strikes-Out Algorithm: A Steady-State Algorithm
                 for Coevolution",
  booktitle =    "Proceedings of the 2006 IEEE Congress on Evolutionary
  year =         "2006",
  editor =       "Gary G. Yen and Simon M. Lucas and Gary Fogel and 
                 Graham Kendall and Ralf Salomon and 
                 Byoung-Tak Zhang and Carlos A. Coello Coello and 
                 Thomas Philip Runarsson",
  pages =        "1639--1646",
  address =      "Vancouver, BC, Canada",
  month =        "16-21 " # jul,
  publisher =    "IEEE Press",
  ISBN =         "0-7803-9487-9",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "",
  URL =          "",
  URL =          "",
  DOI =          "doi:10.1109/CEC.2006.1688505",
  size =         "8 pages",
  abstract =     "We introduce the N-strikes-out algorithm, a simple
                 steady-state genetic algorithm for competitive
                 coevolution. The algorithm can be summarised as
                 follows: Run competitions between randomly chosen
                 individuals, keep track of the number of defeats for
                 each individual, and remove any individual which has
                 been defeated N times. Naive application of the
                 algorithm in 2-population problems leads to severe
                 disengagement. We find that disengagement can be
                 eliminated (for all tasks involving real-valued
                 continuous scores) by determining victories and defeats
                 between fellow members of the same species, using
                 competitions against a single member of the opposing
                 species as a point of comparison. We apply our
                 algorithm to the box-grabbing problem for artificial 3D
                 creatures introduced by Sims. We compare our algorithm
                 with Sims' original Last Elite Opponent algorithm, and
                 describe (and explain) different results obtained with
                 two different implementations differing mainly by the
                 harshness of their selection regimes",
  notes =        "Also known as \cite{1688505}",

Genetic Programming entries for Thomas Miconi Alastair D Channon