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Evolutionary Detection of New Classes of Equilibria: Application in Behavioral Games

机译:新平衡类的进化检测:在行为博弈中的应用

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Standard game theory relies on the assumption that players are rational decision makers that try to maximize their payoffs. Experiments with human players show that real people rarely follow the predictions of normative theory. Our aim is to model the human behavior accurately. Several classes of equilibria (Nash, Pareto, Nash-Pareto and fuzzy Nash-Pareto) are considered by using appropriate generative relations. Three versions of the centipede game are used to illustrate the different types of equilibrium. Based on a study of how people play the centipede game, an equilibrium configuration that models the human behavior is detected. This configuration is a joint equilibrium obtained as a fuzzy combination of Nash and Pareto equilibria. In this way a connection between normative theory, computational game theory and behavioral games is established.
机译:标准博弈论基于这样的假设,即玩家是试图使收益最大化的理性决策者。对人类参与者的实验表明,真实的人很少遵循规范理论的预测。我们的目标是准确地模拟人类行为。通过使用适当的生成关系,可以考虑几类均衡(纳什,帕累托,纳什-帕累托和模糊纳什-帕累托)。 versions游戏的三个版本用于说明平衡的不同类型。基于对人们如何玩ipe游戏的研究,可以检测到模拟人类行为的平衡配置。这种配置是作为纳什和帕累托均衡的模糊组合而获得的联合均衡。这样,建立了规范理论,计算博弈论和行为博弈之间的联系。

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