Asymptotically truthful equilibrium selection in large congestion games

Ryan M. Rogers, Aaron Roth
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引用次数: 45

Abstract

Studying games in the complete information model makes them analytically tractable. However, large n player interactions are more realistically modeled as games of incomplete information, where players may know little to nothing about the types of other players. Unfortunately, games in incomplete information settings lose many of the nice properties of complete information games: the quality of equilibria can become worse, the equilibria lose their ex-post properties, and coordinating on an equilibrium becomes even more difficult. Because of these problems, we would like to study games of incomplete information, but still implement equilibria of the complete information game induced by the (unknown) realized player types. This problem was recently studied by Kearns et al [Kearns et al. 2014], and solved in large games by means of introducing a weak mediator: their mediator took as input reported types of players, and output suggested actions which formed a correlated equilibrium of the underlying game. Players had the option to play independently of the mediator, or ignore its suggestions, but crucially, if they decided to opt-in to the mediator, they did not have the power to lie about their type. In this paper, we rectify this deficiency in the setting of large congestion games. We give, in a sense, the weakest possible mediator: it cannot enforce participation, verify types, or enforce its suggestions. Moreover, our mediator implements a Nash equilibrium of the complete information game. We show that it is an (asymptotic) ex-post equilibrium of the incomplete information game for all players to use the mediator honestly, and that when they do so, they end up playing an approximate Nash equilibrium of the induced complete information game. In particular, truthful use of the mediator is a Bayes-Nash equilibrium in any Bayesian game for any prior.
大拥塞对策的渐近真实均衡选择
在完全信息模型中研究博弈使其易于分析处理。然而,更现实的情况是,n玩家互动是不完全信息的游戏,玩家可能对其他玩家的类型知之甚少。不幸的是,不完全信息环境下的游戏失去了完全信息游戏的许多优点:平衡的质量可能会变得更差,平衡失去了其事后属性,平衡的协调变得更加困难。由于这些问题,我们希望研究不完全信息博弈,但仍然实现由(未知的)已实现参与人类型诱导的完全信息博弈的均衡。最近,Kearns等人研究了这个问题,并通过引入弱中介在大型博弈中解决了这个问题:他们的中介将报告的玩家类型作为输入,输出建议的行动形成了潜在博弈的相关均衡。玩家可以选择独立于调解人进行游戏,或者忽略调解人的建议,但关键是,如果他们决定加入调解人,他们就没有权力谎报自己的类型。在本文中,我们在大型拥堵博弈的设置中纠正了这一缺陷。从某种意义上说,我们给出了最弱的中介:它不能强制参与、验证类型或强制执行其建议。此外,我们的中介实现了完全信息博弈的纳什均衡。我们证明了所有参与者诚实地使用中介是不完全信息博弈的(渐近)前后均衡,并且当他们这样做时,他们最终会达到诱导完全信息博弈的近似纳什均衡。特别是,对于任何先验的任何贝叶斯博弈,真实地使用中介是贝叶斯-纳什均衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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