A Foundation for Markov Equilibria in Sequential Games with Finite Social Memory
研究了无限期界、序贯行动的随机博弈，假设社会记忆有限（除一个玩家外，其他玩家寿命有限且无法观察久远事件），证明只有马尔可夫均衡是可纯化的，对博弈论学者有用。
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. Copyright 2013, Oxford University Press.