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Proper belief revision and rationalizability in dynamic games

机译:动态游戏中正确的信念修正和合理性

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In this paper we develop an epistemic model for dynamic games in which players may revise their beliefs about the opponents' utility functions as the game proceeds. Within this framework, we propose a rationalizability concept that is based upon the following three principles: (1) at every instance of the game, a player should believe that his opponents are carrying out optimal strategies, (2) a player, at information set h, should not change his belief about an opponent's relative ranking of two strategies s and s′ if both s and s′ could have led to h, and (3) the players' initial beliefs about the opponents' utility functions should agree on a given profile u of utility functions. Common belief in these events leads to the concept of persistent rationalizability for the profile u of utility functions. It is shown that for a given game tree with observable deviators and a given profile u of utility functions, every properly point-rationalizable strategy is a persistently rationalizable strategy for u. This result implies that persistently rationalizable strategies always exist for all game trees with observable deviators and all profiles of utility functions. We provide an algorithm that can be used to compute the set of persistently rationalizable strategies for a given profile u of utility functions. For generic games with perfect information, persistent rationalizability uniquely selects the backward induction strategy for every player.
机译:在本文中,我们开发了一种动态游戏的认知模型,其中,随着游戏的进行,玩家可能会改变对对手效用函数的看法。在此框架内,我们提出一个合理性概念,该概念基于以下三个原则:(1)在游戏的每个实例中,玩家都应相信其对手正在执行最佳策略,(2)玩家在信息集上h,如果s和s'两者都可能导致h,则不应改变其对对手相对于两个策略s和s'的排名的信念,并且(3)玩家对对手效用函数的最初信念应就a给定实用程序功能的配置文件u。对这些事件的共同信念导致了效用函数轮廓u的持续合理化的概念。结果表明,对于给定的具有可观察到的偏斜和具有效用函数的给定轮廓u的游戏树,每个适当的点合理化策略都是u的持久合理化策略。该结果表明,对于所有带有可观察到的偏差和效用函数的所有配置文件的游戏树,始终存在持续合理化的策略。我们提供了一种算法,可用于计算给定效用函数u的一组持久合理化策略。对于具有完美信息的通用游戏,持久合理性会为每个玩家唯一地选择向后诱导策略。

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