v1v2v3 (latest)

Learning Near Optimal Policies with Low Inherent Bellman Error

29 February 2020

Mykel Kochenderfer

Papers citing "Learning Near Optimal Policies with Low Inherent Bellman Error"

44 / 94 papers shown

Title
Optimistic Policy Optimization is Provably Efficient in Non-stationary MDPs Han Zhong Zhuoran Yang Zhaoran Wang Csaba Szepesvári 117 21 0 18 Oct 2021
Reward-Free Model-Based Reinforcement Learning with Linear Function Approximation Weitong Zhang Dongruo Zhou Quanquan Gu OffRL 86 28 0 12 Oct 2021
Representation Learning for Online and Offline RL in Low-rank MDPs Masatoshi Uehara Xuezhou Zhang Wen Sun OffRL 140 129 0 09 Oct 2021
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning Andrea Zanette Martin J. Wainwright Emma Brunskill OffRL 100 119 0 19 Aug 2021
Efficient Local Planning with Linear Function Approximation Dong Yin Botao Hao Yasin Abbasi-Yadkori N. Lazić Csaba Szepesvári 132 19 0 12 Aug 2021
Towards General Function Approximation in Zero-Sum Markov Games Baihe Huang Jason D. Lee Zhaoran Wang Zhuoran Yang 88 47 0 30 Jul 2021
Going Beyond Linear RL: Sample Efficient Neural Function Approximation Baihe Huang Kaixuan Huang Sham Kakade Jason D. Lee Qi Lei Runzhe Wang Jiaqi Yang 101 8 0 14 Jul 2021
Adapting to Misspecification in Contextual Bandits Dylan J. Foster Claudio Gentile M. Mohri Julian Zimmert 117 87 0 12 Jul 2021
Variance-Aware Off-Policy Evaluation with Linear Function Approximation Yifei Min Tianhao Wang Dongruo Zhou Quanquan Gu OffRL 89 38 0 22 Jun 2021
Provably Efficient Representation Selection in Low-rank Markov Decision Processes: From Online to Offline RL Weitong Zhang Jiafan He Dongruo Zhou Amy Zhang Quanquan Gu OffRL 72 11 0 22 Jun 2021
Uniform-PAC Bounds for Reinforcement Learning with Linear Function Approximation Jiafan He Dongruo Zhou Quanquan Gu 45 13 0 22 Jun 2021
MADE: Exploration via Maximizing Deviation from Explored Regions Tianjun Zhang Paria Rashidinejad Jiantao Jiao Yuandong Tian Joseph E. Gonzalez Stuart J. Russell OffRL 96 44 0 18 Jun 2021
Randomized Exploration for Reinforcement Learning with General Value Function Approximation Haque Ishfaq Qiwen Cui V. Nguyen Alex Ayoub Zhuoran Yang Zhaoran Wang Doina Precup Lin F. Yang 94 48 0 15 Jun 2021
Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning Tengyang Xie Nan Jiang Huan Wang Caiming Xiong Yu Bai OffRL OnRL 109 165 0 09 Jun 2021
The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces Chi Jin Qinghua Liu Tiancheng Yu 86 50 0 07 Jun 2021
Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs with a Generative Model Bingyan Wang Yuling Yan Jianqing Fan 106 20 0 28 May 2021
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting Gen Li Yuxin Chen Yuejie Chi Yuantao Gu Yuting Wei OffRL 90 30 0 17 May 2021
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation Andrea Zanette Ching-An Cheng Alekh Agarwal 106 53 0 24 Mar 2021
An Exponential Lower Bound for Linearly-Realizable MDPs with Constant Suboptimality Gap Yuanhao Wang Ruosong Wang Sham Kakade OffRL 191 43 0 23 Mar 2021
Bilinear Classes: A Structural Framework for Provable Generalization in RL S. Du Sham Kakade Jason D. Lee Shachar Lovett G. Mahajan Wen Sun Ruosong Wang OffRL 216 191 0 19 Mar 2021
Near-optimal Policy Optimization Algorithms for Learning Adversarial Linear Mixture MDPs Jiafan He Dongruo Zhou Quanquan Gu 139 24 0 17 Feb 2021
Almost Optimal Algorithms for Two-player Zero-Sum Linear Mixture Markov Games Zixiang Chen Dongruo Zhou Quanquan Gu 75 25 0 15 Feb 2021
Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent States Shi Dong Benjamin Van Roy Zhengyuan Zhou 107 32 0 10 Feb 2021
Near-optimal Representation Learning for Linear Bandits and Linear RL Jiachen Hu Xiaoyu Chen Chi Jin Lihong Li Liwei Wang OffRL 165 53 0 08 Feb 2021
Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms Chi Jin Qinghua Liu Sobhan Miryoosefi OffRL 123 220 0 01 Feb 2021
Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP Zihan Zhang Jiaqi Yang Xiangyang Ji S. Du 114 41 0 29 Jan 2021
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 266 169 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 81 46 0 02 Jan 2021
Learning Adversarial Markov Decision Processes with Delayed Feedback Tal Lancewicki Aviv A. Rosenberg Yishay Mansour 109 35 0 29 Dec 2020
Regret Bound Balancing and Elimination for Model Selection in Bandits and RL Aldo Pacchiano Christoph Dann Claudio Gentile Peter L. Bartlett 100 49 0 24 Dec 2020
Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes Dongruo Zhou Quanquan Gu Csaba Szepesvári 110 209 0 15 Dec 2020
Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL Andrea Zanette OffRL 219 71 0 14 Dec 2020
Logarithmic Regret for Reinforcement Learning with Linear Function Approximation Jiafan He Dongruo Zhou Quanquan Gu 60 95 0 23 Nov 2020
Model-based Reinforcement Learning for Continuous Control with Posterior Sampling Ying Fan Yifei Ming 97 18 0 20 Nov 2020
On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces Zhuoran Yang Chi Jin Zhaoran Wang Mengdi Wang Michael I. Jordan 97 18 0 09 Nov 2020
Efficient Learning in Non-Stationary Linear Markov Decision Processes Ahmed Touati Pascal Vincent 108 29 0 24 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 128 107 0 28 Sep 2020
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration Andrea Zanette A. Lazaric Mykel J. Kochenderfer Emma Brunskill 98 64 0 18 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
Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping Dongruo Zhou Jiafan He Quanquan Gu 105 136 0 23 Jun 2020
Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension Ruosong Wang Ruslan Salakhutdinov Lin F. Yang 101 55 0 21 May 2020
Model Selection in Contextual Stochastic Bandit Problems Aldo Pacchiano My Phan Yasin Abbasi-Yadkori Anup B. Rao Julian Zimmert Tor Lattimore Csaba Szepesvári 203 94 0 03 Mar 2020
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang Ruosong Wang S. Du A. Krishnamurthy 191 137 0 09 Dec 2019
Frequentist Regret Bounds for Randomized Least-Squares Value Iteration Andrea Zanette David Brandfonbrener Emma Brunskill Matteo Pirotta A. Lazaric 153 132 0 01 Nov 2019