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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"

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Title
Tactical Optimism and Pessimism for Deep Reinforcement Learning Theodore H. Moskovitz Jack Parker-Holder Aldo Pacchiano Michael Arbel Michael I. Jordan 99 59 0 07 Feb 2021
On Query-efficient Planning in MDPs under Linear Realizability of the Optimal State-value Function Gellert Weisz Philip Amortila Barnabás Janzer Yasin Abbasi-Yadkori Nan Jiang Csaba Szepesvári OffRL 73 20 0 03 Feb 2021
Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms Chi Jin Qinghua Liu Sobhan Miryoosefi OffRL 144 220 0 01 Feb 2021
Fast Rates for the Regret of Offline Reinforcement Learning Yichun Hu Nathan Kallus Masatoshi Uehara OffRL 121 30 0 31 Jan 2021
Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP Zihan Zhang Jiaqi Yang Xiangyang Ji S. Du 116 41 0 29 Jan 2021
Breaking the Deadly Triad with a Target Network Shangtong Zhang Hengshuai Yao Shimon Whiteson AAML 144 45 0 21 Jan 2021
Linear Representation Meta-Reinforcement Learning for Instant Adaptation Matt Peng Banghua Zhu Jiantao Jiao 85 9 0 12 Jan 2021
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 269 169 0 06 Jan 2021
A Provably Efficient Algorithm for Linear Markov Decision Process with Low Switching Cost Minbo Gao Tianle Xie S. Du Lin F. Yang 84 46 0 02 Jan 2021
Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes Dongruo Zhou Quanquan Gu Csaba Szepesvári 113 209 0 15 Dec 2020
Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL Andrea Zanette OffRL 227 71 0 14 Dec 2020
Com-DDPG: A Multiagent Reinforcement Learning-based Offloading Strategy for Mobile Edge Computing Honghao Gao Xuejie Wang Xiaojin Ma Wei Wei S. Mumtaz 16 7 0 09 Dec 2020
Regret Bounds for Adaptive Nonlinear Control Nicholas M. Boffi Stephen Tu Jean-Jacques E. Slotine 103 48 0 26 Nov 2020
Logarithmic Regret for Reinforcement Learning with Linear Function Approximation Jiafan He Dongruo Zhou Quanquan Gu 60 95 0 23 Nov 2020
Reinforcement learning with distance-based incentive/penalty (DIP) updates for highly constrained industrial control systems Hyungju Park Daiki Min Jong-hyun Ryu D. Choi 26 0 0 22 Nov 2020
Model-based Reinforcement Learning for Continuous Control with Posterior Sampling Ying Fan Yifei Ming 97 18 0 20 Nov 2020
Efficient Learning in Non-Stationary Linear Markov Decision Processes Ahmed Touati Pascal Vincent 108 29 0 24 Oct 2020
Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration Priyank Agrawal Jinglin Chen Nan Jiang 117 21 0 23 Oct 2020
Logistic Q-Learning Joan Bas-Serrano Sebastian Curi Andreas Krause Gergely Neu 108 40 0 21 Oct 2020
Nonstationary Reinforcement Learning with Linear Function Approximation Huozhi Zhou Jinglin Chen Lav Varshney A. Jagmohan 95 30 0 08 Oct 2020
Exponential Lower Bounds for Planning in MDPs With Linearly-Realizable Optimal Action-Value Functions Gellert Weisz Philip Amortila Csaba Szepesvári OffRL 169 80 0 03 Oct 2020
Is Reinforcement Learning More Difficult Than Bandits? A Near-optimal Algorithm Escaping the Curse of Horizon Zihan Zhang Xiangyang Ji S. Du OffRL 137 107 0 28 Sep 2020
A Contraction Approach to Model-based Reinforcement Learning Ting-Han Fan Peter J. Ramadge OffRL 55 1 0 18 Sep 2020
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration Andrea Zanette A. Lazaric Mykel J. Kochenderfer Emma Brunskill 101 64 0 18 Aug 2020
Accountable Off-Policy Evaluation With Kernel Bellman Statistics Yihao Feng Zhaolin Ren Ziyang Tang Qiang Liu OffRL 148 44 0 15 Aug 2020
Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation Chen-Yu Wei Mehdi Jafarnia-Jahromi Haipeng Luo Rahul Jain 94 43 0 23 Jul 2020
Efficient Planning in Large MDPs with Weak Linear Function Approximation R. Shariff Csaba Szepesvári 82 22 0 13 Jul 2020
Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning Ming Yin Yu Bai Yu Wang OffRL 100 31 0 07 Jul 2020
Accuracy-Efficiency Trade-Offs and Accountability in Distributed ML Systems A. Feder Cooper K. Levy Christopher De Sa 49 19 0 04 Jul 2020
A Unifying View of Optimism in Episodic Reinforcement Learning Gergely Neu Ciara Pike-Burke 88 67 0 03 Jul 2020
Online learning in MDPs with linear function approximation and bandit feedback Gergely Neu Julia Olkhovskaya 73 33 0 03 Jul 2020
Adaptive Discretization for Model-Based Reinforcement Learning Sean R. Sinclair Tianyu Wang Gauri Jain Siddhartha Banerjee Chao Yu OffRL 81 21 0 01 Jul 2020
Dynamic Regret of Policy Optimization in Non-stationary Environments Yingjie Fei Zhuoran Yang Zhaoran Wang Qiaomin Xie 95 56 0 30 Jun 2020
Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping Dongruo Zhou Jiafan He Quanquan Gu 118 136 0 23 Jun 2020
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret Yingjie Fei Zhuoran Yang Yudong Chen Zhaoran Wang Qiaomin Xie 66 67 0 22 Jun 2020
Provably Efficient Causal Reinforcement Learning with Confounded Observational Data Lingxiao Wang Zhuoran Yang Zhaoran Wang OffRL 86 48 0 22 Jun 2020
On Reward-Free Reinforcement Learning with Linear Function Approximation Ruosong Wang S. Du Lin F. Yang Ruslan Salakhutdinov OffRL 83 107 0 19 Jun 2020
FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs Alekh Agarwal Sham Kakade A. Krishnamurthy Wen Sun OffRL 215 227 0 18 Jun 2020
$Q$ -learning with Logarithmic Regret Kunhe Yang Lin F. Yang S. Du 102 62 0 16 Jun 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning Sebastian Curi Felix Berkenkamp Andreas Krause 132 85 0 15 Jun 2020
A General Framework for Analyzing Stochastic Dynamics in Learning Algorithms Chi-Ning Chou Juspreet Singh Sandhu Mien Brabeeba Wang Tiancheng Yu 71 4 0 11 Jun 2020
Constrained episodic reinforcement learning in concave-convex and knapsack settings Kianté Brantley Miroslav Dudík Thodoris Lykouris Sobhan Miryoosefi Max Simchowitz Aleksandrs Slivkins Wen Sun OffRL 103 52 0 09 Jun 2020
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model Gen Li Yuting Wei Yuejie Chi Yuxin Chen 158 131 0 26 May 2020
Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension Ruosong Wang Ruslan Salakhutdinov Lin F. Yang 109 55 0 21 May 2020
Is Long Horizon Reinforcement Learning More Difficult Than Short Horizon Reinforcement Learning? Ruosong Wang S. Du Lin F. Yang Sham Kakade OffRL 95 52 0 01 May 2020
Kernel-Based Reinforcement Learning: A Finite-Time Analysis O. D. Domingues Pierre Ménard Matteo Pirotta E. Kaufmann Michal Valko 80 18 0 12 Apr 2020
Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning Fei Feng Ruosong Wang W. Yin S. Du Lin F. Yang OffRL SSL 81 7 0 15 Mar 2020
Generative Adversarial Imitation Learning with Neural Networks: Global Optimality and Convergence Rate Yufeng Zhang Qi Cai Zhuoran Yang Zhaoran Wang 221 12 0 08 Mar 2020
Model Selection in Contextual Stochastic Bandit Problems Aldo Pacchiano My Phan Yasin Abbasi-Yadkori Anup B. Rao Julian Zimmert Tor Lattimore Csaba Szepesvári 205 94 0 03 Mar 2020
Provably Efficient Safe Exploration via Primal-Dual Policy Optimization Dongsheng Ding Xiaohan Wei Zhuoran Yang Zhaoran Wang M. Jovanović 127 166 0 01 Mar 2020