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Provably Efficient Reinforcement Learning with Linear Function Approximation

11 July 2019

Papers citing "Provably Efficient Reinforcement Learning with Linear Function Approximation"

50 / 417 papers shown

Title
Provable Reward-Agnostic Preference-Based Reinforcement Learning Wenhao Zhan Masatoshi Uehara Wen Sun Jason D. Lee 76 11 0 29 May 2023
Reinforcement Learning with Human Feedback: Learning Dynamic Choices via Pessimism Zihao Li Zhuoran Yang Mengdi Wang OffRL 109 60 0 29 May 2023
The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning Kaiwen Wang Kevin Zhou Runzhe Wu Nathan Kallus Wen Sun OffRL 84 19 0 25 May 2023
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice Toshinori Kitamura Tadashi Kozuno Yunhao Tang Nino Vieillard Michal Valko ... Olivier Pietquin Matthieu Geist Csaba Szepesvári Wataru Kumagai Yutaka Matsuo OffRL 90 3 0 22 May 2023
Offline Primal-Dual Reinforcement Learning for Linear MDPs Germano Gabbianelli Gergely Neu Nneka Okolo Matteo Papini OffRL 85 8 0 22 May 2023
On the Statistical Efficiency of Mean Field Reinforcement Learning with General Function Approximation Jiawei Huang Batuhan Yardim Niao He 98 11 0 18 May 2023
Optimistic Natural Policy Gradient: a Simple Efficient Policy Optimization Framework for Online RL Qinghua Liu Gellert Weisz András Gyorgy Chi Jin Csaba Szepesvári OffRL 82 9 0 18 May 2023
Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning Gen Li Wenhao Zhan Jason D. Lee Yuejie Chi Yuxin Chen OffRL OnRL 152 13 0 17 May 2023
Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage Jose H. Blanchet Miao Lu Tong Zhang Han Zhong OffRL 126 32 0 16 May 2023
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes Han Zhong Tong Zhang 101 29 0 15 May 2023
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs Kaixuan Ji Qingyue Zhao Jiafan He Weitong Zhang Q. Gu 109 4 0 15 May 2023
Uniform-PAC Guarantees for Model-Based RL with Bounded Eluder Dimension Yue Wu Jiafan He Quanquan Gu 51 2 0 15 May 2023
Delay-Adapted Policy Optimization and Improved Regret for Adversarial MDP with Delayed Bandit Feedback Tal Lancewicki Aviv A. Rosenberg Dmitry Sotnikov 55 3 0 13 May 2023
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation Yifei Min Jiafan He Tianhao Wang Quanquan Gu 111 9 0 10 May 2023
What can online reinforcement learning with function approximation benefit from general coverage conditions? Fanghui Liu Luca Viano Volkan Cevher OffRL 68 3 0 25 Apr 2023
Long-Term Fairness with Unknown Dynamics Tongxin Yin Reilly P. Raab M. Liu Yang Liu FaML 96 28 0 19 Apr 2023
Minimax-Optimal Reward-Agnostic Exploration in Reinforcement Learning Gen Li Yuling Yan Yuxin Chen Jianqing Fan OffRL 126 12 0 14 Apr 2023
Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL Zakaria Mhammedi Dylan J. Foster Alexander Rakhlin 108 18 0 12 Apr 2023
Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding Zhaolin Ren Tongzheng Ren Haitong Ma Na Li Bo Dai 107 10 0 08 Apr 2023
Does Sparsity Help in Learning Misspecified Linear Bandits? Jialin Dong Lin F. Yang 73 1 0 29 Mar 2023
Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs Yuan Cheng Ruiquan Huang J. Yang Yitao Liang OffRL 76 8 0 20 Mar 2023
Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs Junkai Zhang Weitong Zhang Quanquan Gu 64 3 0 17 Mar 2023
Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning Xutong Zhao Yangchen Pan Chenjun Xiao Sarath Chandar Janarthanan Rajendran 95 6 0 16 Mar 2023
Provably Efficient Model-Free Algorithms for Non-stationary CMDPs Honghao Wei A. Ghosh Ness B. Shroff Lei Ying Xingyu Zhou 76 15 0 10 Mar 2023
Foundation Models for Decision Making: Problems, Methods, and Opportunities Sherry Yang Ofir Nachum Yilun Du Jason W. Wei Pieter Abbeel Dale Schuurmans LM&Ro OffRL LRM AI4CE 203 172 0 07 Mar 2023
Revisiting Weighted Strategy for Non-stationary Parametric Bandits Jing Wang Peng Zhao Zhihong Zhou 57 6 0 05 Mar 2023
Finite-sample Guarantees for Nash Q-learning with Linear Function Approximation Pedro Cisneros-Velarde Oluwasanmi Koyejo 85 1 0 01 Mar 2023
The Provable Benefits of Unsupervised Data Sharing for Offline Reinforcement Learning Haotian Hu Yiqin Yang Qianchuan Zhao Chongjie Zhang OffRL 77 7 0 27 Feb 2023
Exponential Hardness of Reinforcement Learning with Linear Function Approximation Daniel M. Kane Sihan Liu Shachar Lovett G. Mahajan Csaba Szepesvári Gellert Weisz 94 4 0 25 Feb 2023
VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation Thanh Nguyen-Tang R. Arora OffRL 94 5 0 24 Feb 2023
Provably Efficient Reinforcement Learning via Surprise Bound Hanlin Zhu Ruosong Wang Jason D. Lee OffRL 65 5 0 22 Feb 2023
Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret Han Zhong Jiachen Hu Yecheng Xue Tongyang Li Liwei Wang 68 8 0 21 Feb 2023
Reinforcement Learning in a Birth and Death Process: Breaking the Dependence on the State Space Jonatha Anselmi B. Gaujal Louis-Sébastien Rebuffi 74 2 0 21 Feb 2023
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency Heyang Zhao Jiafan He Dongruo Zhou Tong Zhang Quanquan Gu 106 28 0 21 Feb 2023
Reinforcement Learning with Function Approximation: From Linear to Nonlinear Jihao Long Jiequn Han 72 6 0 20 Feb 2023
Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learning Bhargav Ganguly Yulian Wu Di Wang Vaneet Aggarwal 60 9 0 16 Feb 2023
Breaking the Curse of Multiagency: Provably Efficient Decentralized Multi-Agent RL with Function Approximation Yuanhao Wang Qinghua Liu Yunru Bai Chi Jin 105 28 0 13 Feb 2023
A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints Ming Shi Yitao Liang Ness B. Shroff 86 9 0 08 Feb 2023
Near-Optimal Adversarial Reinforcement Learning with Switching Costs Ming Shi Yitao Liang Ness B. Shroff 70 2 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 Jianchao Tan S. Du 129 24 0 07 Feb 2023
Offline Learning in Markov Games with General Function Approximation Yuheng Zhang Yunru Bai Nan Jiang OffRL 104 9 0 06 Feb 2023
Reinforcement Learning in Low-Rank MDPs with Density Features Audrey Huang Jinglin Chen Nan Jiang OffRL 88 14 0 04 Feb 2023
Robust Fitted-Q-Evaluation and Iteration under Sequentially Exogenous Unobserved Confounders David Bruns-Smith Angela Zhou OffRL 76 10 0 01 Feb 2023
Learning in POMDPs is Sample-Efficient with Hindsight Observability Jonathan Lee Alekh Agarwal Christoph Dann Tong Zhang 65 21 0 31 Jan 2023
A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence Carlo Alfano Rui Yuan Patrick Rebeschini 147 15 0 30 Jan 2023
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation Uri Sherman Tomer Koren Yishay Mansour 93 12 0 30 Jan 2023
Refined Regret for Adversarial MDPs with Linear Function Approximation Yan Dai Haipeng Luo Chen-Yu Wei Julian Zimmert 112 12 0 30 Jan 2023
STEERING: Stein Information Directed Exploration for Model-Based Reinforcement Learning Souradip Chakraborty Amrit Singh Bedi Alec Koppel Mengdi Wang Furong Huang Dinesh Manocha 74 8 0 28 Jan 2023
Model-based Offline Reinforcement Learning with Local Misspecification Kefan Dong Yannis Flet-Berliac Allen Nie Emma Brunskill OffRL 70 4 0 26 Jan 2023
Exploration in Model-based Reinforcement Learning with Randomized Reward Lingxiao Wang Ping Li 72 0 0 09 Jan 2023