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A Foundation for Markov Equilibria in Sequential Games with Finite Social Memory

机译:具有有限社会记忆的顺序博弈中的马尔可夫均衡基础

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摘要

We study stochastic games with an infinite horizon and sequential moves played by an arbitrary number of players. We assume that social memory is finite-every player, except possibly one, is finitely lived and cannot observe events that are sufficiently far back in the past. This class of games includes games between a long-run player and a sequence of short-run players, and games with overlapping generations of players. An equilibrium is purifiable if some close-by behaviour is consistent with equilibrium when agents' payoffs in each period are perturbed additively and independently. We show that only Markov equilibria are purifiable when social memory is finite. Thus if a game has at most one long-run player, all purifiable equilibria are Markov.
机译:我们研究具有无限视野和任意数量玩家连续玩法的随机游戏。我们假设社交记忆是有限的每一个人,但可能除外,它是有限地存在的,无法观察到过去足够远的事件。此类游戏包括长期玩家和一系列短期玩家之间的游戏,以及具有重叠世代玩家的游戏。如果每个时期的代理人的支出受到累加且独立的扰动,如果某些近距离行为与均衡相一致,则均衡是可纯化的。我们证明,当社会记忆力有限时,只有马尔可夫均衡是可以净化的。因此,如果一个游戏最多只有一位长期玩家,则所有可净化的平衡点都是马尔可夫。

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