Almost Optimal Algorithms for Two-player Zero-Sum Linear Mixture Markov Games

15 February 2021

Quanquan Gu

Papers citing "Almost Optimal Algorithms for Two-player Zero-Sum Linear Mixture Markov Games"

26 / 26 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 92 2 0 13 Feb 2025
Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes Dongruo Zhou Quanquan Gu Csaba Szepesvári 68 207 0 15 Dec 2020
Minimax Sample Complexity for Turn-based Stochastic Game Qiwen Cui Lin F. Yang 33 23 0 29 Nov 2020
Logarithmic Regret for Reinforcement Learning with Linear Function Approximation Jiafan He Dongruo Zhou Quanquan Gu 51 93 0 23 Nov 2020
A Sharp Analysis of Model-based Reinforcement Learning with Self-Play Qinghua Liu Tiancheng Yu Yu Bai Chi Jin 86 122 0 04 Oct 2020
Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping Dongruo Zhou Jiafan He Quanquan Gu 61 135 0 23 Jun 2020
Near-Optimal Reinforcement Learning with Self-Play Yunru Bai Chi Jin Tiancheng Yu 158 132 0 22 Jun 2020
Model-Free Reinforcement Learning: from Clipped Pseudo-Regret to Sample Complexity Zihan Zhang Yuanshuo Zhou Xiangyang Ji 49 35 0 06 Jun 2020
Model-Based Reinforcement Learning with Value-Targeted Regression Alex Ayoub Zeyu Jia Csaba Szepesvári Mengdi Wang Lin F. Yang OffRL 83 304 0 01 Jun 2020
Learning Near Optimal Policies with Low Inherent Bellman Error Andrea Zanette A. Lazaric Mykel Kochenderfer Emma Brunskill OffRL 71 222 0 29 Feb 2020
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium Qiaomin Xie Yudong Chen Zhaoran Wang Zhuoran Yang 141 125 0 17 Feb 2020
Provable Self-Play Algorithms for Competitive Reinforcement Learning Yu Bai Chi Jin SSL 134 149 0 10 Feb 2020
Provably Efficient Exploration in Policy Optimization Qi Cai Zhuoran Yang Chi Jin Zhaoran Wang 51 281 0 12 Dec 2019
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang Ruosong Wang S. Du A. Krishnamurthy 168 136 0 09 Dec 2019
Frequentist Regret Bounds for Randomized Least-Squares Value Iteration Andrea Zanette David Brandfonbrener Emma Brunskill Matteo Pirotta A. Lazaric 62 130 0 01 Nov 2019
Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles Aditya Modi Nan Jiang Ambuj Tewari Satinder Singh 63 131 0 23 Oct 2019
Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity Aaron Sidford Mengdi Wang Lin F. Yang Yinyu Ye 87 70 0 29 Aug 2019
Provably Efficient Reinforcement Learning with Linear Function Approximation Chi Jin Zhuoran Yang Zhaoran Wang Michael I. Jordan 86 557 0 11 Jul 2019
Feature-Based Q-Learning for Two-Player Stochastic Games Zeyu Jia Lin F. Yang Mengdi Wang 73 45 0 02 Jun 2019
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound Lin F. Yang Mengdi Wang OffRL GP 55 286 0 24 May 2019
A Theoretical Analysis of Deep Q-Learning Jianqing Fan Zhuoran Yang Yuchen Xie Zhaoran Wang 177 605 0 01 Jan 2019
Is Q-learning Provably Efficient? Chi Jin Zeyuan Allen-Zhu Sébastien Bubeck Michael I. Jordan OffRL 63 806 0 10 Jul 2018
Online Reinforcement Learning in Stochastic Games Chen-Yu Wei Yi-Te Hong Chi-Jen Lu OffRL 67 120 0 02 Dec 2017
Minimax Regret Bounds for Reinforcement Learning M. G. Azar Ian Osband Rémi Munos 83 774 0 16 Mar 2017
Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving Shai Shalev-Shwartz Shaked Shammah Amnon Shashua 104 834 0 11 Oct 2016
Value Function Approximation in Zero-Sum Markov Games M. Lagoudakis Ronald E. Parr OffRL 62 78 0 12 Dec 2012