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A Novel Dynamic Decision Model in 2-player Symmetric Repeated Games

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Considering the dynamic character of repeated games and M arkov process, this paper presented a novel dynamic decision model for symmetric repeated games. In this model, players' actions were mapped to a Markov decision process with payoffs, and the Boltzmann distribution was into iduced. Our dynamic model is different from others' , we used this dynamic model to study the iterated prisoner' s dilemma, and the results show that this decision model can successfully be used in symmetric repeated games and has an ability of adaptive learning.

game theoryevolutionary gamerepeated gameMarkov processdecision model

Liu Weibing、Wang Xianjia、Wang Guangmin

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Institute of Systems Engineering, Wuhan University, Wuhan 430072 ,China

School of Management, China University Of Geosciences, Wuhan 430074 ,China

2008

Engineering sciences

Engineering sciences

ISSN:1672-4178
年,卷(期):2008.6(1)