Subgame Maxmin Strategies in Zero-Sum Stochastic Games with Tolerance Levels

We study subgame phi-maxmin strategies in two-player zero-sum stochastic games with a countable state space, finite action spaces, and a bounded and universally measurable payoff function. Here, phi denotes the tolerance function that assigns a nonnegative tolerated error level to every subgame. Subgame f-maxmin strategies are strategies of the maximizing player that guarantee the lower value in every subgame within the subgame-dependent tolerance level as given by phi. First, we provide necessary and sufficient conditions for a strategy to be a subgame phi-maxmin strategy. As a special case, we obtain a characterization for subgame maxmin strategies, i.e., strategies that exactly guarantee the lower value at every subgame. Secondly, we present sufficient conditions for the existence of a subgame f-maxmin strategy. Finally, we show the possibly surprising result that each game admits a strictly positive tolerance function phi* with the following property: if a player has a subgame phi*-maxmin strategy, then he has a subgame maxmin strategy too. As a consequence, the existence of a subgame phi-maxmin strategy for every positive tolerance function f is equivalent to the existence of a subgame maxmin strategy.