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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Multiobjective Evolution of Mixed Nash Equilibria
verfasst von : David Iclănzan, Noémi Gaskó, Réka Nagy, D. Dumitrescu
Erschienen in: Learning and Intelligent Optimization
Verlag: Springer Berlin Heidelberg
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Abstract
In a mixed strategy equilibrium players randomize between their actions according to a very specific probability distribution, even though with regard to the game payoff, they are indifferent between their actions. Currently, there is no compelling model explaining why and how agents may randomize their decisions is such a way, in real world scenarios.
We experiment with a model for two player games, where the goal of the players is to find robust strategies for which the uncertainty in the outcome of the opponent is reduced as much as possible. We show that in an evolutionary setting, the proposed model converges to mixed strategy profiles, if these exist. The results suggest that only local knowledge of the game is sufficient to attain the adaptive convergence.