Evolving a Team

by

Haynes, T., Sen, S., Schoenefeld, D. and Wainwright, R.

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Info: Working Notes for the AAAI Symposium on Genetic Programming (Conference proceedings), 1995, p. 23-30
Keywords:genetic algorithms, genetic programming
Abstract:
We introduce a cooperative co--evolutionary system to facilitate the development of teams of agents. Specifically, we deal with the credit assignment problem [CA] of how to fairly split the fitness of a team to all of its participants. We believe that $k$ different strategies for controlling the actions of a group of $k$ agents can combine to form a cooperation strategy which efficiently results in attaining a global goal. A concern is the amount of time needed to either evolve a good team or reach convergence. We present several crossover mechanisms to reduce this time. Even with this mechanisms, the time is large; which precluded the gathering of sufficient data for a statistical base.
Notes:
AAAI-95f GP {\em Telephone:} 415-328-3123 {\em Fax:} 415-321-4457 {\em email} info@aaai.org {\em URL:} http://www.aaai.org/
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BibTex:
@InProceedings{Haynes95:Team,
  author =       "Thomas Haynes and Sandip Sen and Dale Schoenefeld and
                 Roger Wainwright",
  title =        "Evolving a Team",
  booktitle =    "Working Notes for the AAAI Symposium on Genetic
                 Programming",
  year =         "1995",
  editor =       "E. V. Siegel and J. R. Koza",
  pages =        "23--30",
  address =      "MIT, Cambridge, MA, USA",
  publisher_address = "445 Burgess Drive, Menlo Park, CA 94025, USA",
  month =        "10--12 " # nov,
  publisher =    "AAAI",
  keywords =     "genetic algorithms, genetic programming",
  abstract =     "We introduce a cooperative co--evolutionary system to
                 facilitate the development of teams of agents.
                 Specifically, we deal with the credit assignment
                 problem of how to fairly split the fitness of a team to
                 all of its participants. We believe that ${k}$
                 different strategies for controlling the actions of a
                 group of ${k}$ agents can combine to form a cooperation
                 strategy which efficiently results in attaining a
                 global goal. A concern is the amount of time needed to
                 either evolve a good team or reach convergence. We
                 present several crossover mechanisms to reduce this
                 time. Even with this mechanisms, the time is large;
                 which precluded the gathering of sufficient data for a
                 statistical base.",
  notes =        "AAAI-95f GP

                 {\em Telephone:} 415-328-3123 {\em Fax:} 415-321-4457
                 {\em email} info@aaai.org {\em URL:}
                 http://www.aaai.org/",
}