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Refined Sample Complexity for Markov Games with Independent Linear Function Approximation.

, , and . CoRR, (2024)

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Minimax sample complexity for turn-based stochastic game., and . UAI, volume 161 of Proceedings of Machine Learning Research, page 1496-1504. AUAI Press, (2021)Learning in Congestion Games with Bandit Feedback., , , and . NeurIPS, (2022)Provably Efficient Offline Multi-agent Reinforcement Learning via Strategy-wise Bonus., and . NeurIPS, (2022)Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning., , , , , and . CoRR, (2023)Minimax Sample Complexity for Turn-based Stochastic Game., and . CoRR, (2020)Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation., , and . COLT, volume 195 of Proceedings of Machine Learning Research, page 2651-2652. PMLR, (2023)Offline Congestion Games: How Feedback Type Affects Data Coverage Requirement., , , , and . ICLR, OpenReview.net, (2023)Randomized Exploration in Reinforcement Learning with General Value Function Approximation., , , , , , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 4607-4616. PMLR, (2021)A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning., , , , and . CoRR, (2023)NG+ : A Multi-Step Matrix-Product Natural Gradient Method for Deep Learning., , , , and . CoRR, (2021)