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Multiplicative Optimism for Constant Regret in Games
AS

Ashkan Soleymani, Georgios Piliouras

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ResearcharXiv cs.LG

Multiplicative Optimism for Constant Regret in Games

arXiv:2609.21976v1 Announce Type: cross Abstract: 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 combines a potential-based regret-matching argument with multiplicative stability and Hellinger control of strategy movement. A learning-rate safeguard additionally gives $O(\sqrt{T\log d})$ regret in the face of adversarial utilities.

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This story was published by arXiv cs.LG and written by Ashkan Soleymani, Georgios Piliouras. SyncAI.news shows a preview; the complete article is on the publisher's site.

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