Optimal strategies of the iterated prisoner's dilemma problem for multiple conflicting objectives

Authors:
Shashi Mittal;Kalyanmoy Deb
Affiliations:
Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA;Department of Business Technology, Helsinki School of Economics, Helsinki, Finland and Indian Institute of Technology Kanpur, Kanpur, India
Venue:
IEEE Transactions on Evolutionary Computation
Year:
2009

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Abstract

In this paper, we present a new paradigm of searching optimal strategies in the game of iterated prisoner's dilemma (IPD) using multiple-objective evolutionary algorithms. This method is more useful than the existing approaches, because it not only produces strategies that perform better in the iterated game but also finds a family of nondominated strategies, which can be analyzed to decipher properties a strategy should have to win the game in a more satisfactory manner. We present the results obtained by this new method and discuss substrategies found to be common among nondominated strategies. The multiobjective treatment of the IPD problem demonstrated here can be applied to other similar game-playing tasks.