Oblivious equilibrium for general stochastic games with many players

Abstract—This paper studies a solution concept for large stochastic games. A standard solution concept for a stochastic game is Markov perfect equilibrium (MPE). In MPE, each player’s optimal action depends on his own state and the state of the other players. By contrast, oblivious equilibrium (OE) is an approxima-tion introduced in [5] where each player makes decisions based on his own state and the “average ” state of the other players. For this reason OE is computationally more tractable than MPE. It was shown in [5] that as the number of players becomes large, OE closely approximates MPE; however, this result was established under a set of assumptions specific to industry dynamic models. In this paper we develop a parsimonious set of assumptions under which the result of [5] can be generalized to a broader class of stochastic games with a large number of players. I