Co-evolutionary Strategies for an Alternating-Offer Bargaining Problem

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Jin:2005:CIG,
  author =       "Nanlin Jin and Edward Tsang",
  title =        "Co-evolutionary Strategies for an Alternating-Offer
                 Bargaining Problem",
  booktitle =    "IEEE 2005 Symposium on Computational Intelligence and
                 Games CIG'05",
  year =         "2005",
  editor =       "Graham Kendall and Simon Lucas",
  pages =        "211--217",
  email =        "njin@essex.ac.uk, edward@essex.ac.uk",
  address =      "Essex, UK",
  month =        "4-6 " # apr,
  organisation = "Computational Intelligence Society",
  publisher =    "IEEE Press",
  URL =          "http://cswww.essex.ac.uk/Research/CSP/finance/papers/JinTsa-Bargaining-Cig2005.pdf",
  size =         "7 pages",
  keywords =     "genetic algorithms, genetic programming, Co-evolution,
                 GP, Bargaining Theory",
  abstract =     "We apply an Evolutionary Algorithm (EA) to solve the
                 Rubinstein's Basic Alternating-Offer Bargaining
                 Problem, and compare our experimental results with its
                 analytic game-theoretic solution. The application of EA
                 employs an alternative set of assumptions on the
                 players' behaviours. Experimental outcomes suggest that
                 the applied co-evolutionary algorithm, one of
                 Evolutionary Algorithms, is able to generate convincing
                 approximations of the theoretic solutions. The major
                 advantages of EA over the game-theoretic analysis are
                 its flexibility and ease of application to variants of
                 Rubinstein Bargaining Problems and complicated
                 bargaining situations for which theoretic solutions are
                 unavailable.",
}

Genetic Programming entries for Nanlin Jin Edward P K Tsang

Citations