Raman Arora
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2026
Minimax-Optimal Policy Regret in Partially Observable Markov Games
The paper develops an optimistic maximum-likelihood algorithm that achieves $ ilde{O}(\sqrt{T})$ policy regret for sequential decision-making in partially observable Markov games against adaptive opponents.
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