Towards General Function Approximation in Zero-Sum Markov Games

30 July 2021

Papers citing "Towards General Function Approximation in Zero-Sum Markov Games"

36 / 36 papers shown

Title
Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games Tong Yang Bo Dai Lin Xiao Yuejie Chi OffRL 61 2 0 13 Feb 2025
Locally Interdependent Multi-Agent MDP: Theoretical Framework for Decentralized Agents with Dynamic Dependencies Alex DeWeese Guannan Qu 32 2 0 10 Jun 2024
Provably Efficient Information-Directed Sampling Algorithms for Multi-Agent Reinforcement Learning Qiaosheng Zhang Chenjia Bai Shuyue Hu Zhen Wang Xuelong Li 39 1 0 30 Apr 2024
RL in Markov Games with Independent Function Approximation: Improved Sample Complexity Bound under the Local Access Model Junyi Fan Yuxuan Han Jialin Zeng Jian-Feng Cai Yang Wang Yang Xiang Jiheng Zhang 37 1 0 18 Mar 2024
Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation Yu Chen Xiangcheng Zhang Siwei Wang Longbo Huang 39 3 0 28 Feb 2024
Refined Sample Complexity for Markov Games with Independent Linear Function Approximation Yan Dai Qiwen Cui S. S. Du 44 1 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 29 6 0 08 Feb 2024
Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints Dan Qiao Yu-Xiang Wang OffRL 24 3 0 02 Feb 2024
Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence Beyond the Minty Property Ioannis Anagnostides Ioannis Panageas Gabriele Farina T. Sandholm 33 3 0 19 Dec 2023
Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-Constraint Wei Xiong Hanze Dong Chen Ye Ziqi Wang Han Zhong Heng Ji Nan Jiang Tong Zhang OffRL 38 161 0 18 Dec 2023
Sample-Efficient Multi-Agent RL: An Optimization Perspective Nuoya Xiong Zhihan Liu Zhaoran Wang Zhuoran Yang 38 1 0 10 Oct 2023
Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games Songtao Feng Ming Yin Yu-Xiang Wang J. Yang Yitao Liang 36 0 0 17 Aug 2023
Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration Zhihan Liu Miao Lu Wei Xiong Han Zhong Haotian Hu Shenao Zhang Sirui Zheng Zhuoran Yang Zhaoran Wang OffRL 32 22 0 29 May 2023
On the Statistical Efficiency of Mean Field Reinforcement Learning with General Function Approximation Jiawei Huang Batuhan Yardim Niao He 42 10 0 18 May 2023
Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit Feedback Yang Cai Haipeng Luo Chen-Yu Wei Weiqiang Zheng 26 17 0 05 Mar 2023
Breaking the Curse of Multiagency: Provably Efficient Decentralized Multi-Agent RL with Function Approximation Yuanhao Wang Qinghua Liu Yunru Bai Chi Jin 27 28 0 13 Feb 2023
Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning Volodymyr Tkachuk Seyed Alireza Bakhtiari Johannes Kirschner Matej Jusup Ilija Bogunovic Csaba Szepesvári 24 4 0 08 Feb 2023
Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation Qiwen Cui Kaipeng Zhang S. Du 28 23 0 07 Feb 2023
Population-size-Aware Policy Optimization for Mean-Field Games Pengdeng Li Xinrun Wang Shuxin Li Hau Chan Bo An 21 2 0 07 Feb 2023
Offline Learning in Markov Games with General Function Approximation Yuheng Zhang Yunru Bai Nan Jiang OffRL 18 8 0 06 Feb 2023
A Reduction-based Framework for Sequential Decision Making with Delayed Feedback Yunchang Yang Hangshi Zhong Tianhao Wu B. Liu Liwei Wang S. Du OffRL 27 8 0 03 Feb 2023
Smoothing Policy Iteration for Zero-sum Markov Games Yangang Ren Yao Lyu Wenxuan Wang Sheng Li Zeyang Li Jingliang Duan 31 1 0 03 Dec 2022
Provably Efficient Model-free RL in Leader-Follower MDP with Linear Function Approximation A. Ghosh 17 1 0 28 Nov 2022
A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games Wei Xiong Han Zhong Chengshuai Shi Cong Shen Tong Zhang 66 18 0 04 Oct 2022
Learning Two-Player Mixture Markov Games: Kernel Function Approximation and Correlated Equilibrium C. J. Li Dongruo Zhou Quanquan Gu Michael I. Jordan 21 2 0 10 Aug 2022
A Deep Reinforcement Learning Approach for Finding Non-Exploitable Strategies in Two-Player Atari Games Zihan Ding DiJia Su Qinghua Liu Chi Jin 33 3 0 18 Jul 2022
Policy Optimization for Markov Games: Unified Framework and Faster Convergence Runyu Zhang Qinghua Liu Haiquan Wang Caiming Xiong Na Li Yu Bai 21 26 0 06 Jun 2022
Provably Efficient Offline Multi-agent Reinforcement Learning via Strategy-wise Bonus Qiwen Cui S. Du OffRL 18 19 0 01 Jun 2022
Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets Han Zhong Wei Xiong Jiyuan Tan Liwei Wang Tong Zhang Zhaoran Wang Zhuoran Yang OffRL 19 37 0 15 Feb 2022
Independent Policy Gradient for Large-Scale Markov Potential Games: Sharper Rates, Function Approximation, and Game-Agnostic Convergence Dongsheng Ding Chen-Yu Wei Kaipeng Zhang M. Jovanović 22 69 0 08 Feb 2022
Near-Optimal Learning of Extensive-Form Games with Imperfect Information Yunru Bai Chi Jin Song Mei Tiancheng Yu 21 26 0 03 Feb 2022
Independent Learning in Stochastic Games Asuman Ozdaglar M. O. Sayin Kaipeng Zhang 16 22 0 23 Nov 2021
When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently? Ziang Song Song Mei Yu Bai 74 67 0 08 Oct 2021
Online Sub-Sampling for Reinforcement Learning with General Function Approximation Dingwen Kong Ruslan Salakhutdinov Ruosong Wang Lin F. Yang OffRL 38 1 0 14 Jun 2021
Understanding the Eluder Dimension Gen Li Pritish Kamath Dylan J. Foster Nathan Srebro 22 11 0 14 Apr 2021
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang Ruosong Wang S. Du A. Krishnamurthy 135 135 0 09 Dec 2019