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2102.07404
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Almost Optimal Algorithms for Two-player Zero-Sum Linear Mixture Markov Games
International Conference on Algorithmic Learning Theory (ALT), 2021
15 February 2021
Zixiang Chen
Dongruo Zhou
Quanquan Gu
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Papers citing
"Almost Optimal Algorithms for Two-player Zero-Sum Linear Mixture Markov Games"
19 / 19 papers shown
Distributionally Robust Online Markov Game with Linear Function Approximation
Zewu Zheng
Yuanyuan Lin
OOD
OffRL
359
0
0
11 Nov 2025
Sample-Efficient Distributionally Robust Multi-Agent Reinforcement Learning via Online Interaction
Zain Ulabedeen Farhat
Debamita Ghosh
George Atia
Yue Wang
233
2
0
04 Aug 2025
Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games
Tong Yang
Bo Dai
Lin Xiao
Yuejie Chi
OffRL
477
4
0
13 Feb 2025
Provably Efficient Information-Directed Sampling Algorithms for Multi-Agent Reinforcement Learning
Qiaosheng Zhang
Chenjia Bai
Shuyue Hu
Zhen Wang
Xuelong Li
337
2
0
30 Apr 2024
Refined Sample Complexity for Markov Games with Independent Linear Function Approximation
Annual Conference Computational Learning Theory (COLT), 2024
Yan Dai
Qiwen Cui
S. S. Du
417
2
0
11 Feb 2024
Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL
Jiawei Huang
Niao He
Andreas Krause
417
8
0
08 Feb 2024
Sample-Efficient Multi-Agent RL: An Optimization Perspective
International Conference on Learning Representations (ICLR), 2023
Nuoya Xiong
Zhihan Liu
Zhaoran Wang
Zhuoran Yang
322
2
0
10 Oct 2023
Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games
International Conference on Machine Learning (ICML), 2023
Songtao Feng
Ming Yin
Yu Wang
J. Yang
Yitao Liang
190
1
0
17 Aug 2023
On the Statistical Efficiency of Mean Field Reinforcement Learning with General Function Approximation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Jiawei Huang
Batuhan Yardim
Niao He
518
15
0
18 May 2023
Can We Find Nash Equilibria at a Linear Rate in Markov Games?
International Conference on Learning Representations (ICLR), 2023
Zhuoqing Song
Jason D. Lee
Zhuoran Yang
448
10
0
03 Mar 2023
Finite-sample Guarantees for Nash Q-learning with Linear Function Approximation
Conference on Uncertainty in Artificial Intelligence (UAI), 2023
Pedro Cisneros-Velarde
Oluwasanmi Koyejo
349
3
0
01 Mar 2023
Breaking the Curse of Multiagency: Provably Efficient Decentralized Multi-Agent RL with Function Approximation
Annual Conference Computational Learning Theory (COLT), 2023
Yuanhao Wang
Qinghua Liu
Yunru Bai
Chi Jin
360
39
0
13 Feb 2023
Offline Learning in Markov Games with General Function Approximation
International Conference on Machine Learning (ICML), 2023
Yuheng Zhang
Yunru Bai
Nan Jiang
OffRL
385
14
0
06 Feb 2023
Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model
Neural Information Processing Systems (NeurIPS), 2022
Gen Li
Yuejie Chi
Yuting Wei
Yuxin Chen
435
20
0
22 Aug 2022
Learning Two-Player Mixture Markov Games: Kernel Function Approximation and Correlated Equilibrium
C. J. Li
Dongruo Zhou
Quanquan Gu
Sai Li
187
2
0
10 Aug 2022
Policy Optimization for Markov Games: Unified Framework and Faster Convergence
Neural Information Processing Systems (NeurIPS), 2022
Runyu Zhang
Qinghua Liu
Haiquan Wang
Caiming Xiong
Na Li
Yu Bai
471
31
0
06 Jun 2022
One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Pedro Cisneros-Velarde
Boxiang Lyu
Oluwasanmi Koyejo
Mladen Kolar
OffRL
475
3
0
31 May 2022
Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation
International Conference on Machine Learning (ICML), 2022
Pier Giuseppe Sessa
Maryam Kamgarpour
Andreas Krause
296
22
0
14 Mar 2022
Near-Optimal Learning of Extensive-Form Games with Imperfect Information
International Conference on Machine Learning (ICML), 2022
Yunru Bai
Chi Jin
Song Mei
Tiancheng Yu
401
30
0
03 Feb 2022
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