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Truncated Noisy Best-Response Algorithms: Toward Game Theoretic Learning with Safety Guarantees
We consider a game theoretic approach to solve multi-agent coordination problems with submodular maximization objectives. It is known for such problems that the Nash equilibria for the corresponding game are always within 50% of the optimal, but that the equilibria which achieve this worst-case boun
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