Co-evolutionary Strategies for an Alternating-Offer Bargaining Problem

Created by W.Langdon from gp-bibliography.bib Revision:1.7642

@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