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Zero-sum stochastic games are easy to solve as they can be cast as simple Markov decision processes.
Equilibrium points in n-person games
J. F. Nash · 1950
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On the computation of equilibria in discounted stochastic dynamic games
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A two-stage feasible directions algorithm for nonlinear constrained optimization
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Engineering Optimization: Theory and Practice
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LDL, a Concise Sparse Cholesky Package , November 2007
T. A. Davis · 2007
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Multi-agent reinforcement learning: Algorithm converging to Nash equilibrium in general-sum stochastic games
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Solving stochastic games
L. Mac Dermed and C. L. Isbell · 2009
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A user’s guide to solving dynamic stochastic games using the homotopy method
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Stationary equilibria in stochastic games: Structure, selection, and computation
P. Herings and R.J.A.P. Peeters · 2004
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