Provable Self-Play Algorithms for Competitive Reinforcement Learning

10 February 2020

Papers citing "Provable Self-Play Algorithms for Competitive Reinforcement Learning"

47 / 47 papers shown

Title
Refined Sample Complexity for Markov Games with Independent Linear Function Approximation Yan Dai Qiwen Cui S. S. Du 47 1 0 11 Feb 2024
Multi-Player Zero-Sum Markov Games with Networked Separable Interactions Chanwoo Park Kaipeng Zhang Asuman Ozdaglar 30 8 0 13 Jul 2023
A New Policy Iteration Algorithm For Reinforcement Learning in Zero-Sum Markov Games Anna Winnicki R. Srikant 34 1 0 17 Mar 2023
Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit Feedback Yang Cai Haipeng Luo Chen-Yu Wei Weiqiang Zheng 29 17 0 05 Mar 2023
Can We Find Nash Equilibria at a Linear Rate in Markov Games? Zhuoqing Song Jason D. Lee Zhuoran Yang 29 8 0 03 Mar 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 29 4 0 08 Feb 2023
Offline Learning in Markov Games with General Function Approximation Yuheng Zhang Yunru Bai Nan Jiang OffRL 21 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
Provably Efficient Model-free RL in Leader-Follower MDP with Linear Function Approximation A. Ghosh 25 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
Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games Shicong Cen Yuejie Chi S. Du Lin Xiao 59 35 0 03 Oct 2022
$$O(T^{-1})$ Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games$ $O(T^{-1})$ Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games Yuepeng Yang Cong Ma 37 14 0 26 Sep 2022
Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model Gen Li Yuejie Chi Yuting Wei Yuxin Chen 32 18 0 22 Aug 2022
Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions Shuang Qiu Xiaohan Wei Jieping Ye Zhaoran Wang Zhuoran Yang OffRL 30 11 0 25 Jul 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
On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL Jinglin Chen Aditya Modi A. Krishnamurthy Nan Jiang Alekh Agarwal 38 25 0 21 Jun 2022
A Survey on Model-based Reinforcement Learning Fan Luo Tian Xu Hang Lai Xiong-Hui Chen Weinan Zhang Yang Yu OffRL LRM 50 101 0 19 Jun 2022
Policy Optimization for Markov Games: Unified Framework and Faster Convergence Runyu Zhang Qinghua Liu Haiquan Wang Caiming Xiong Na Li Yu Bai 27 26 0 06 Jun 2022
Learning in Congestion Games with Bandit Feedback Qiwen Cui Zhihan Xiong Maryam Fazel S. Du 26 12 0 04 Jun 2022
Sample-Efficient Reinforcement Learning of Partially Observable Markov Games Qinghua Liu Csaba Szepesvári Chi Jin 40 20 0 02 Jun 2022
The Complexity of Markov Equilibrium in Stochastic Games C. Daskalakis Noah Golowich Kaipeng Zhang 36 57 0 08 Apr 2022
Learning Markov Games with Adversarial Opponents: Efficient Algorithms and Fundamental Limits Qinghua Liu Yuanhao Wang Chi Jin AAML 29 15 0 14 Mar 2022
Versatile Dueling Bandits: Best-of-both-World Analyses for Online Learning from Preferences Aadirupa Saha Pierre Gaillard 36 8 0 14 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
When is Offline Two-Player Zero-Sum Markov Game Solvable? Qiwen Cui S. Du OffRL 33 29 0 10 Jan 2022
Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopic Followers? Han Zhong Zhuoran Yang Zhaoran Wang Michael I. Jordan 29 30 0 27 Dec 2021
Finite-Sample Analysis of Decentralized Q-Learning for Stochastic Games Zuguang Gao Qianqian Ma Tamer Bacsar J. Birge OffRL 22 7 0 15 Dec 2021
Efficient and Optimal Algorithms for Contextual Dueling Bandits under Realizability Aadirupa Saha A. Krishnamurthy 34 35 0 24 Nov 2021
Independent Learning in Stochastic Games Asuman Ozdaglar M. O. Sayin Kaipeng Zhang 16 22 0 23 Nov 2021
Dueling RL: Reinforcement Learning with Trajectory Preferences Aldo Pacchiano Aadirupa Saha Jonathan Lee 33 81 0 08 Nov 2021
On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning Weichao Mao Lin F. Yang Kaipeng Zhang Tamer Bacsar 39 57 0 12 Oct 2021
Provably Efficient Reinforcement Learning in Decentralized General-Sum Markov Games Weichao Mao Tamer Basar 31 66 0 12 Oct 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
Towards General Function Approximation in Zero-Sum Markov Games Baihe Huang Jason D. Lee Zhaoran Wang Zhuoran Yang 33 47 0 30 Jul 2021
Strategically Efficient Exploration in Competitive Multi-agent Reinforcement Learning R. Loftin Aadirupa Saha Sam Devlin Katja Hofmann 30 5 0 30 Jul 2021
Model-Free Learning for Two-Player Zero-Sum Partially Observable Markov Games with Perfect Recall Tadashi Kozuno Pierre Ménard Rémi Munos Michal Valko 30 18 0 11 Jun 2021
The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces Chi Jin Qinghua Liu Tiancheng Yu 26 50 0 07 Jun 2021
Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning Sebastian Curi Ilija Bogunovic Andreas Krause 39 17 0 18 Mar 2021
Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games Yu Bai Chi Jin Haiquan Wang Caiming Xiong 44 67 0 23 Feb 2021
Last-iterate Convergence of Decentralized Optimistic Gradient Descent/Ascent in Infinite-horizon Competitive Markov Games Chen-Yu Wei Chung-Wei Lee Mengxiao Zhang Haipeng Luo 25 82 0 08 Feb 2021
Exploration-Exploitation in Multi-Agent Learning: Catastrophe Theory Meets Game Theory Stefanos Leonardos Georgios Piliouras 31 40 0 05 Dec 2020
Online Learning in Unknown Markov Games Yi Tian Yuanhao Wang Tiancheng Yu S. Sra OffRL 17 13 0 28 Oct 2020
A Sharp Analysis of Model-based Reinforcement Learning with Self-Play Qinghua Liu Tiancheng Yu Yu Bai Chi Jin 32 121 0 04 Oct 2020
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity Kaipeng Zhang Sham Kakade Tamer Bacsar Lin F. Yang 47 119 0 15 Jul 2020
Near-Optimal Reinforcement Learning with Self-Play Yunru Bai Chi Jin Tiancheng Yu 19 129 0 22 Jun 2020
Linear Last-iterate Convergence in Constrained Saddle-point Optimization Chen-Yu Wei Chung-Wei Lee Mengxiao Zhang Haipeng Luo 19 11 0 16 Jun 2020
Reward-Free Exploration for Reinforcement Learning Chi Jin A. Krishnamurthy Max Simchowitz Tiancheng Yu OffRL 112 194 0 07 Feb 2020