Layered Learning for Evolving Goal Scoring Behavior in Soccer Players

Created by W.Langdon from gp-bibliography.bib Revision:1.4333

  title =        "Layered Learning for Evolving Goal Scoring Behavior in
                 Soccer Players",
  author =       "Andrei Bajurnow and Vic Ciesielski",
  pages =        "1828--1835",
  booktitle =    "Proceedings of the 2004 IEEE Congress on Evolutionary
  year =         "2004",
  publisher =    "IEEE Press",
  month =        "20-23 " # jun,
  address =      "Portland, Oregon",
  ISBN =         "0-7803-8515-2",
  URL =          "",
  DOI =          "doi:10.1109/CEC.2004.1331118",
  size =         "8 pages",
  keywords =     "genetic algorithms, genetic programming, Evolutionary
                 intelligent agents, Evolutionary Computation and
  abstract =     "Layered learning allows decomposition of the stages of
                 learning in a problem domain. We apply this technique
                 to the evolution of goal scoring behavior in soccer
                 players and show that layered learning is able to find
                 solutions comparable to standard genetic programs more
                 reliably. The solutions evolved with layers have a
                 higher accuracy but do not make as many goal attempts.
                 We compared three variations of layered learning and
                 find that maintaining the population between layers as
                 the encapsulated learnt layer is introduced to be the
                 most computationally efficient. The quality of
                 solutions found by layered learning did not exceed
                 those of standard genetic programming in terms of goal
                 scoring ability.",
  notes =        "CEC 2004 - A joint meeting of the IEEE, the EPS, and
                 the IEE.",

Genetic Programming entries for Andrei Bajurnow Victor Ciesielski