Co-evolutionary Strategies for an Alternating-Offer Bargaining Problem

Created by W.Langdon from gp-bibliography.bib Revision:1.4202

  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 =        ",",
  address =      "Essex, UK",
  month =        "4-6 " # apr,
  organisation = "Computational Intelligence Society",
  publisher =    "IEEE Press",
  URL =          "",
  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

Genetic Programming entries for Nanlin Jin Edward P K Tsang