Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning

9 June 2021

Huan Wang

Papers citing "Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning"

50 / 50 papers shown

Title
MILE: Model-based Intervention Learning Yigit Korkmaz Erdem Bıyık 112 2 0 21 Feb 2025
On The Statistical Complexity of Offline Decision-Making Thanh Nguyen-Tang R. Arora OffRL 140 1 0 10 Jan 2025
Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration Max Wilcoxson Qiyang Li Kevin Frans Sergey Levine SSL OffRL OnRL 124 0 0 23 Oct 2024
Leveraging Unlabeled Data Sharing through Kernel Function Approximation in Offline Reinforcement Learning Yen-Ru Lai Fu-Chieh Chang Pei-Yuan Wu OffRL 98 1 0 22 Aug 2024
Settling the Sample Complexity of Online Reinforcement Learning Zihan Zhang Yuxin Chen Jason D. Lee S. Du OffRL 125 22 0 25 Jul 2023
On Bonus-Based Exploration Methods in the Arcade Learning Environment Adrien Ali Taïga W. Fedus Marlos C. Machado Aaron Courville Marc G. Bellemare 40 59 0 22 Sep 2021
Nearly Horizon-Free Offline Reinforcement Learning Tongzheng Ren Jialian Li Bo Dai S. Du Sujay Sanghavi OffRL 61 49 0 25 Mar 2021
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism Paria Rashidinejad Banghua Zhu Cong Ma Jiantao Jiao Stuart J. Russell OffRL 156 284 0 22 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 99 189 0 19 Mar 2021
MUSBO: Model-based Uncertainty Regularized and Sample Efficient Batch Optimization for Deployment Constrained Reinforcement Learning DiJia Su Jason D. Lee John M. Mulvey H. Vincent Poor OffRL 26 6 0 23 Feb 2021
Near-Optimal Offline Reinforcement Learning via Double Variance Reduction Ming Yin Yu Bai Yu Wang OffRL 51 67 0 02 Feb 2021
Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms Chi Jin Qinghua Liu Sobhan Miryoosefi OffRL 76 216 0 01 Feb 2021
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 177 167 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 48 46 0 02 Jan 2021
Is Pessimism Provably Efficient for Offline RL? Ying Jin Zhuoran Yang Zhaoran Wang OffRL 105 352 0 30 Dec 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 59 18 0 09 Nov 2020
Learning Quadrupedal Locomotion over Challenging Terrain Joonho Lee Jemin Hwangbo Lorenz Wellhausen V. Koltun Marco Hutter 92 1,154 0 21 Oct 2020
Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited O. D. Domingues Pierre Ménard E. Kaufmann Michal Valko 38 96 0 07 Oct 2020
A Sharp Analysis of Model-based Reinforcement Learning with Self-Play Qinghua Liu Tiancheng Yu Yu Bai Chi Jin 58 122 0 04 Oct 2020
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration Andrea Zanette A. Lazaric Mykel J. Kochenderfer Emma Brunskill 55 64 0 18 Aug 2020
Provably Good Batch Reinforcement Learning Without Great Exploration Yao Liu Adith Swaminathan Alekh Agarwal Emma Brunskill OffRL 89 105 0 16 Jul 2020
Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning Ming Yin Yu Bai Yu Wang OffRL 75 31 0 07 Jul 2020
Near-Optimal Reinforcement Learning with Self-Play Yunru Bai Chi Jin Tiancheng Yu 121 131 0 22 Jun 2020
FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs Alekh Agarwal Sham Kakade A. Krishnamurthy Wen Sun OffRL 92 225 0 18 Jun 2020
Conservative Q-Learning for Offline Reinforcement Learning Aviral Kumar Aurick Zhou George Tucker Sergey Levine OffRL OnRL 104 1,780 0 08 Jun 2020
Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization T. Matsushima Hiroki Furuta Y. Matsuo Ofir Nachum S. Gu OffRL 43 147 0 05 Jun 2020
MOPO: Model-based Offline Policy Optimization Tianhe Yu G. Thomas Lantao Yu Stefano Ermon James Zou Sergey Levine Chelsea Finn Tengyu Ma OffRL 67 759 0 27 May 2020
MOReL : Model-Based Offline Reinforcement Learning Rahul Kidambi Aravind Rajeswaran Praneeth Netrapalli Thorsten Joachims OffRL 75 662 0 12 May 2020
Almost Optimal Model-Free Reinforcement Learning via Reference-Advantage Decomposition Zihan Zhang Yuanshuo Zhou Xiangyang Ji OffRL 53 156 0 21 Apr 2020
Q* Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison Tengyang Xie Nan Jiang 58 35 0 09 Mar 2020
Learning Near Optimal Policies with Low Inherent Bellman Error Andrea Zanette A. Lazaric Mykel Kochenderfer Emma Brunskill OffRL 63 222 0 29 Feb 2020
Behavior Regularized Offline Reinforcement Learning Yifan Wu George Tucker Ofir Nachum OffRL 68 678 0 26 Nov 2019
Solving Rubik's Cube with a Robot Hand OpenAI Ilge Akkaya Marcin Andrychowicz Maciek Chociej Ma-teusz Litwin ... Peter Welinder Lilian Weng Qiming Yuan Wojciech Zaremba Lei Zhang ODL 73 1,215 0 16 Oct 2019
Emergent Tool Use From Multi-Agent Autocurricula Bowen Baker I. Kanitscheider Todor Markov Yi Wu Glenn Powell Bob McGrew Igor Mordatch LRM 64 649 0 17 Sep 2019
Benchmarking Bonus-Based Exploration Methods on the Arcade Learning Environment Adrien Ali Taïga W. Fedus Marlos C. Machado Aaron Courville Marc G. Bellemare 49 40 0 06 Aug 2019
Provably Efficient Reinforcement Learning with Linear Function Approximation Chi Jin Zhuoran Yang Zhaoran Wang Michael I. Jordan 79 549 0 11 Jul 2019
When to Trust Your Model: Model-Based Policy Optimization Michael Janner Justin Fu Marvin Zhang Sergey Levine OffRL 57 939 0 19 Jun 2019
Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction Aviral Kumar Justin Fu George Tucker Sergey Levine OffRL OnRL 79 1,044 0 03 Jun 2019
Provably Efficient Q-Learning with Low Switching Cost Yu Bai Tengyang Xie Nan Jiang Yu Wang 39 93 0 30 May 2019
Information-Theoretic Considerations in Batch Reinforcement Learning Jinglin Chen Nan Jiang OOD OffRL 93 373 0 01 May 2019
Off-Policy Deep Reinforcement Learning without Exploration Scott Fujimoto David Meger Doina Precup OffRL BDL 157 1,586 0 07 Dec 2018
Policy Certificates: Towards Accountable Reinforcement Learning Christoph Dann Ashutosh Adhikari Wei Wei Jimmy J. Lin OffRL 94 142 0 07 Nov 2018
Is Q-learning Provably Efficient? Chi Jin Zeyuan Allen-Zhu Sébastien Bubeck Michael I. Jordan OffRL 52 801 0 10 Jul 2018
QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation Dmitry Kalashnikov A. Irpan P. Pastor Julian Ibarz Alexander Herzog ... Deirdre Quillen E. Holly Mrinal Kalakrishnan Vincent Vanhoucke Sergey Levine 98 1,454 0 27 Jun 2018
Rainbow: Combining Improvements in Deep Reinforcement Learning Matteo Hessel Joseph Modayil H. V. Hasselt Tom Schaul Georg Ostrovski Will Dabney Dan Horgan Bilal Piot M. G. Azar David Silver OffRL 94 2,255 0 06 Oct 2017
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning Christoph Dann Tor Lattimore Emma Brunskill 62 307 0 22 Mar 2017
Minimax Regret Bounds for Reinforcement Learning M. G. Azar Ian Osband Rémi Munos 68 771 0 16 Mar 2017
Contextual Decision Processes with Low Bellman Rank are PAC-Learnable Nan Jiang A. Krishnamurthy Alekh Agarwal John Langford Robert Schapire 90 417 0 29 Oct 2016
Model-based Reinforcement Learning and the Eluder Dimension Ian Osband Benjamin Van Roy 65 188 0 07 Jun 2014
Empirical Bernstein Bounds and Sample Variance Penalization Andreas Maurer Massimiliano Pontil 167 540 0 21 Jul 2009