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The Complexity of Infinite-Horizon General-Sum Stochastic Games

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arxiv 2204.04186 v2 pith:45M27OQX submitted 2022-04-08 cs.GT cs.CCcs.DSmath.OC

classification cs.GTcs.CCcs.DSmath.OC
keywords gamescomputingstochasticplayercomplexitygeneral-suminfinite-horizonppad-hard
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We study the complexity of computing stationary Nash equilibrium (NE) in n-player infinite-horizon general-sum stochastic games. We focus on the problem of computing NE in such stochastic games when each player is restricted to choosing a stationary policy and rewards are discounted. First, we prove that computing such NE is in PPAD (in addition to clearly being PPAD-hard). Second, we consider turn-based specializations of such games where at each state there is at most a single player that can take actions and show that these (seemingly-simpler) games remain PPAD-hard. Third, we show that under further structural assumptions on the rewards computing NE in such turn-based games is possible in polynomial time. Towards achieving these results we establish structural facts about stochastic games of broader utility, including monotonicity of utilities under single-state single-action changes and reductions to settings where each player controls a single state.

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  1. Solving Zero-Sum Convex Markov Games

    cs.GT 2025-06 conditional novelty 7.0 of 10

    Independent policy-gradient algorithms provably compute approximate Nash equilibria in two-player zero-sum convex Markov games.

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