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Evaluating Deterministic Policies in Two-player Iterated Games

Evaluating Deterministic Policies in Two-player Iterated Games

This video was recorded at 4th European Conference on Complex Systems. We construct a statistical ensemble of games, where in each independent subensemble we have two players playing the same game. We derive the mean payoffs per move of the representative players of the game, and we evaluate all the deterministic policies with finite memory. In particular,we show that if one of the players has a generalized tit-for-tat policy,the mean payoff per move of both players is the same, forcing the equalization of the mean payoffs per move of both players. In the case of symmetric, non-cooperative and dilemmatic games, we show that generalized tit-for-tat or imitation policies together with the condition of not being the first to defect, leads to the highest mean payoffs per move for the players. Within this approach, it can be decided which policies perform better than others.The Prisoner's Dilemma and the Hawk-Dove games have been analyzed,and the equilibrium states of the infinitely iterated games have been determined. The infinitely iterated Prisoner's Dilemma game can have Nash solutions only if players have deterministic policies.


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