论文标题

顺序游戏中颤抖的完美和相关性

Trembling-Hand Perfection and Correlation in Sequential Games

论文作者

Marchesi, Alberto, Gatti, Nicola

论文摘要

我们启动了与相关性的连续(即广泛形式)游戏中颤抖的完美的研究。我们引入了广泛的完美相关平衡(EFPCE),作为经典广泛形式相关平衡(EFCE)的改进,该平衡(EFCE)修改了其弱点。这是通过考虑玩家在游戏的每个信息集中独立遵循建议时犯错误的可能性来实现的。在提供了EFPCE的公理定义后,我们表明,由于任何完美(NASH)均衡构成EFPCE,因此总是存在一个,并且它是EFCE的完善,因为任何EFPCE也是EFCE。然后,我们证明,令人惊讶的是,计算EFPCE并不比找到EFCE更难,因为可以在多项式时间内解决该问题,用于一般的N-N-Player广泛形式游戏(也有机会)。这是通过将问题制定为找到限制解决方案的问题(如$ε\ rightarrow 0 $)来实现的,以适当定义的颤抖的LP参数为$ε$,以指数为代表许多变量,并且在多个方面的约束中。为此,我们展示了如何将最近开发的用于颤抖LP的多项式时间算法适应有指数级变量的问题。这要求解决(非交换)LP的序列,具有指数的许多变量,并且在多项式上有许多约束,这在多项式时间中可以通过对希望方法应用椭圆形进行。

We initiate the study of trembling-hand perfection in sequential (i.e., extensive-form) games with correlation. We introduce the extensive-form perfect correlated equilibrium (EFPCE) as a refinement of the classical extensive-form correlated equilibrium (EFCE) that amends its weaknesses off the equilibrium path. This is achieved by accounting for the possibility that players may make mistakes while following recommendations independently at each information set of the game. After providing an axiomatic definition of EFPCE, we show that one always exists since any perfect (Nash) equilibrium constitutes an EFPCE, and that it is a refinement of EFCE, as any EFPCE is also an EFCE. Then, we prove that, surprisingly, computing an EFPCE is not harder than finding an EFCE, since the problem can be solved in polynomial time for general n-player extensive-form games (also with chance). This is achieved by formulating the problem as that of finding a limit solution (as $ε\rightarrow 0$) to a suitably defined trembling LP parametrized by $ε$, featuring exponentially many variables and polynomially many constraints. To this end, we show how a recently developed polynomial-time algorithm for trembling LPs can be adapted to deal with problems having an exponential number of variables. This calls for the solution of a sequence of (non-trembling) LPs with exponentially many variables and polynomially many constraints, which is possible in polynomial time by applying an ellipsoid against hope approach.

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