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Optimal Strategies of the Iterated Prisoner's Dilemma Problem for Multiple Conflicting Objectives

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2 Author(s)
Mittal, S. ; Oper. Res. Center, Massachusetts Inst. of Technol., Cambridge, MA ; Deb, K.

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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Evolutionary Computation, IEEE Transactions on  (Volume:13 ,  Issue: 3 )