Equilibrium Selection by Co-evolution for Bargaining Problems under Incomplete Information about Time Preferences

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{NanlinJin:2005:CEC,

• author = "Nanlin Jin",
• title = "Equilibrium Selection by Co-evolution for Bargaining Problems under Incomplete Information about Time Preferences",
• booktitle = "Proceedings of the 2005 IEEE Congress on Evolutionary Computation",
• year = "2005",
• editor = "David Corne and Zbigniew Michalewicz and Marco Dorigo and Gusz Eiben and David Fogel and Carlos Fonseca and Garrison Greenwood and Tan Kay Chen and Guenther Raidl and Ali Zalzala and Simon Lucas and Ben Paechter and Jennifier Willies and Juan J. Merelo Guervos and Eugene Eberbach and Bob McKay and Alastair Channon and Ashutosh Tiwari and L. Gwenn Volkert and Dan Ashlock and Marc Schoenauer",
• volume = "3",
• pages = "2661--2668",
• address = "Edinburgh, UK",
• month = "2-5 " # sep,
• organization = "IEEE",
• publisher = "IEEE Press",
• email = "njin@essex.ac.uk",
• keywords = "genetic algorithms, genetic programming, co-evolution, game theory",
• ISBN = "0-7803-9363-5",
• URL = "http://cswww.essex.ac.uk/Research/CSP/finance/papers/Jin-IncompleteInfo-Cec2005.pdf",
• DOI = "doi:10.1109/CEC.2005.1555028",
• size = "8 pages",
• abstract = "The main purpose of this work is to measure the impact of players' information completeness on the outcomes in dynamic strategic games. We apply Co-evolutionary Algorithms to solve four incomplete information bargaining problems and investigate the experimental outcomes on players' shares from agreements, the efficiency of agreements and the evolutionary time for convergence. Empirical analyses indicate that in the absence of complete information on the counterpart(s)' preferences, co-evolving populations are still able to select equilibriums which are Pareto-efficient and stationary. This property of the co-evolutionary algorithm supports its future applications on complex dynamic games.",
• notes = "CEC2005 - A joint meeting of the IEEE, the EPS, and the IEE.",

}

Genetic Programming entries for Nanlin Jin

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