Machine Learning Department
School of Computer Science, Carnegie Mellon University
Finding Correlated Equilibria in General Sum Stochastic Games
Chris Murray, Geoff Gordon
Our new algorithm is based on the planning algorithm of . That algorithm computes subgame-perfect Nash equilibria, but assumes that it is given a set of "punishment policies" as input. Our new algorithm requires only the description of the game, an important improvement since suitable punishment policies may be difficult to come by.
 Chris Murray and Geoff Gordon. Multi-robot negotiation: Approximating the set of subgame perfect equilibria in general-sum stochastic games. In NIPS, 2006.
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