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Multiplicative Optimism for Constant Regret in Games

Soleymani, Ashkan et al.
arXiv (All) · Papers
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computer-science-and-game-theorymachine-learningoptimization-and-control
We introduce Multiplicatively Optimistic Regret Matching (MORM), an uncoupled learning rule for finite general-sum games. Under simultaneous full-information self-play, every player achieves external regret $O(\sqrt n\log d)$ uniformly over all horizons, using only one-step optimism. The analysis co
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