Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms

1 February 2021

Papers citing "Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms"

50 / 51 papers shown

Title
Can RLHF be More Efficient with Imperfect Reward Models? A Policy Coverage Perspective Jiawei Huang Bingcong Li Christoph Dann Niao He OffRL 82 0 0 20 May 2025
Decision Making in Hybrid Environments: A Model Aggregation Approach Haolin Liu Chen-Yu Wei Julian Zimmert 86 0 0 09 Feb 2025
Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation Long-Fei Li Yu-Jie Zhang Peng Zhao Zhi-Hua Zhou 101 4 0 17 Jan 2025
Mean-Field Sampling for Cooperative Multi-Agent Reinforcement Learning Emile Anand Ishani Karmarkar Guannan Qu 83 1 0 01 Dec 2024
Sharp Analysis for KL-Regularized Contextual Bandits and RLHF Heyang Zhao Chenlu Ye Quanquan Gu Tong Zhang OffRL 57 3 0 07 Nov 2024
Second Order Bounds for Contextual Bandits with Function Approximation Aldo Pacchiano 53 4 0 24 Sep 2024
The Central Role of the Loss Function in Reinforcement Learning Kaiwen Wang Nathan Kallus Wen Sun OffRL 51 7 0 19 Sep 2024
Random Latent Exploration for Deep Reinforcement Learning Srinath Mahankali Zhang-Wei Hong Ayush Sekhari Alexander Rakhlin Pulkit Agrawal 33 3 0 18 Jul 2024
Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond Xutong Liu Siwei Wang Jinhang Zuo Han Zhong Xuchuang Wang Zhiyong Wang Shuai Li Mohammad Hajiesmaili J. C. Lui Wei Chen 85 1 0 03 Jun 2024
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm Miao Lu Han Zhong Tong Zhang Jose H. Blanchet OffRL OOD 73 4 0 04 Apr 2024
Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation Yu Chen Xiangcheng Zhang Siwei Wang Longbo Huang 34 3 0 28 Feb 2024
No-Regret Reinforcement Learning in Smooth MDPs Davide Maran Alberto Maria Metelli Matteo Papini Marcello Restell 33 5 0 06 Feb 2024
Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent Yingru Li Jiawei Xu Lei Han Zhi-Quan Luo BDL OffRL 26 6 0 05 Feb 2024
A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees Toshinori Kitamura Tadashi Kozuno Masahiro Kato Yuki Ichihara Soichiro Nishimori Akiyoshi Sannai Sho Sonoda Wataru Kumagai Yutaka Matsuo 39 2 0 31 Jan 2024
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling, and Beyond Thanh Nguyen-Tang Raman Arora OffRL 30 3 0 06 Jan 2024
The Effective Horizon Explains Deep RL Performance in Stochastic Environments Cassidy Laidlaw Banghua Zhu Stuart J. Russell Anca Dragan 28 2 0 13 Dec 2023
When is Agnostic Reinforcement Learning Statistically Tractable? Zeyu Jia Gene Li Alexander Rakhlin Ayush Sekhari Nathan Srebro OffRL 27 5 0 09 Oct 2023
The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions Nishil Patel Sebastian Lee Stefano Sarao Mannelli Sebastian Goldt Adrew Saxe OffRL 28 3 0 17 Jun 2023
Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs Yuan-Chia Cheng Ruiquan Huang J. Yang Yitao Liang OffRL 41 8 0 20 Mar 2023
Provably Efficient Reinforcement Learning via Surprise Bound Hanlin Zhu Ruosong Wang Jason D. Lee OffRL 20 5 0 22 Feb 2023
Offline Learning in Markov Games with General Function Approximation Yuheng Zhang Yunru Bai Nan Jiang OffRL 15 8 0 06 Feb 2023
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation Uri Sherman Tomer Koren Yishay Mansour 32 12 0 30 Jan 2023
Tight Guarantees for Interactive Decision Making with the Decision-Estimation Coefficient Dylan J. Foster Noah Golowich Yanjun Han OffRL 25 29 0 19 Jan 2023
Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes Chen Ye Wei Xiong Quanquan Gu Tong Zhang 25 29 0 12 Dec 2022
Provably Efficient Model-free RL in Leader-Follower MDP with Linear Function Approximation A. Ghosh 15 1 0 28 Nov 2022
Linear Reinforcement Learning with Ball Structure Action Space Zeyu Jia Randy Jia Dhruv Madeka Dean Phillips Foster 20 1 0 14 Nov 2022
When is Realizability Sufficient for Off-Policy Reinforcement Learning? Andrea Zanette OffRL 16 14 0 10 Nov 2022
A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games Wei Xiong Han Zhong Chengshuai Shi Cong Shen Tong Zhang 63 18 0 04 Oct 2022
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning Christoph Dann M. Mohri Tong Zhang Julian Zimmert OffRL 18 32 0 23 Aug 2022
A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation P. Amortila Nan Jiang Dhruv Madeka Dean Phillips Foster 13 5 0 18 Jul 2022
PAC Reinforcement Learning for Predictive State Representations Wenhao Zhan Masatoshi Uehara Wen Sun Jason D. Lee 31 38 0 12 Jul 2022
Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems Masatoshi Uehara Ayush Sekhari Jason D. Lee Nathan Kallus Wen Sun OffRL 49 31 0 24 Jun 2022
On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL Jinglin Chen Aditya Modi A. Krishnamurthy Nan Jiang Alekh Agarwal 35 25 0 21 Jun 2022
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity Alekh Agarwal Tong Zhang 39 22 0 15 Jun 2022
Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information Yonathan Efroni Dylan J. Foster Dipendra Kumar Misra A. Krishnamurthy John Langford OffRL 29 25 0 09 Jun 2022
Sample-Efficient Reinforcement Learning of Partially Observable Markov Games Qinghua Liu Csaba Szepesvári Chi Jin 34 20 0 02 Jun 2022
Stabilizing Q-learning with Linear Architectures for Provably Efficient Learning Andrea Zanette Martin J. Wainwright OOD 34 5 0 01 Jun 2022
When Is Partially Observable Reinforcement Learning Not Scary? Qinghua Liu Alan Chung Csaba Szepesvári Chi Jin 14 92 0 19 Apr 2022
Offline Reinforcement Learning Under Value and Density-Ratio Realizability: The Power of Gaps Jinglin Chen Nan Jiang OffRL 21 33 0 25 Mar 2022
Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism Ming Yin Yaqi Duan Mengdi Wang Yu-Xiang Wang OffRL 32 65 0 11 Mar 2022
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets Yifei Min Tianhao Wang Ruitu Xu Zhaoran Wang Michael I. Jordan Zhuoran Yang 33 21 0 07 Mar 2022
Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning Approach Xuezhou Zhang Yuda Song Masatoshi Uehara Mengdi Wang Alekh Agarwal Wen Sun OffRL 24 57 0 31 Jan 2022
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection Matteo Papini Andrea Tirinzoni Aldo Pacchiano Marcello Restelli A. Lazaric Matteo Pirotta 19 18 0 27 Oct 2021
Bad-Policy Density: A Measure of Reinforcement Learning Hardness David Abel Cameron Allen Dilip Arumugam D Ellis Hershkowitz Michael L. Littman Lawson L. S. Wong 23 2 0 07 Oct 2021
Understanding Domain Randomization for Sim-to-real Transfer Xiaoyu Chen Jiachen Hu Chi Jin Lihong Li Liwei Wang 24 112 0 07 Oct 2021
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning Andrea Zanette Martin J. Wainwright Emma Brunskill OffRL 29 111 0 19 Aug 2021
Towards General Function Approximation in Zero-Sum Markov Games Baihe Huang Jason D. Lee Zhaoran Wang Zhuoran Yang 25 47 0 30 Jul 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 24 28 0 17 May 2021
Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP Zihan Zhang Jiaqi Yang Xiangyang Ji S. Du 65 36 0 29 Jan 2021
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang Ruosong Wang S. Du A. Krishnamurthy 132 135 0 09 Dec 2019