Optimal Strategies of the Iterated Prisonerapos;s Dilemma Problem for Multiple Conflicting Objectives
Mittal, S.; Deb, K.
Evolutionary Computation, IEEE Transactions on
Volume 13, Issue 3, June 2009 Page(s):554 - 565
Digital Object Identifier   10.1109/TEVC.2008.2009459
Summary: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 sub-strategies 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.

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