A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning

Neural Information Processing Systems (NeurIPS), 2022

23 August 2022

Tong Zhang

Papers citing "A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning"

29 / 29 papers shown

Title
Variance-Aware Feel-Good Thompson Sampling for Contextual Bandits Xuheng Li Quanquan Gu 60 0 0 03 Nov 2025
No-Regret Thompson Sampling for Finite-Horizon Markov Decision Processes with Gaussian Processes Jasmine Bayrooti Sattar Vakili Amanda Prorok Carl Henrik Ek 76 0 0 23 Oct 2025
Q-learning with Posterior Sampling Priyank Agrawal Shipra Agrawal Azmat Azati OffRL GP 230 1 0 01 Jun 2025
When a Reinforcement Learning Agent Encounters Unknown Unknowns Juntian Zhu Miguel de Carvalho Zhouwang Yang Fengxiang He 227 0 0 19 May 2025
A Single Goal is All You Need: Skills and Exploration Emerge from Contrastive RL without Rewards, Demonstrations, or SubgoalsInternational Conference on Learning Representations (ICLR), 2024 Grace Liu Michael Tang Benjamin Eysenbach OffRL 351 8 0 11 Aug 2024
Misspecified $Q$ -Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation Error Ally Yalei Du Lin F. Yang Ruosong Wang 186 0 0 18 Jul 2024
Satisficing Exploration for Deep Reinforcement Learning Dilip Arumugam Saurabh Kumar Ramki Gummadi Benjamin Van Roy 208 3 0 16 Jul 2024
More Efficient Randomized Exploration for Reinforcement Learning via Approximate Sampling Haque Ishfaq Yixin Tan Yu Yang Qingfeng Lan Jianfeng Lu A. Rupam Mahmood Doina Precup Pan Xu 158 8 0 18 Jun 2024
Bayesian Design Principles for Offline-to-Online Reinforcement Learning Haotian Hu Yiqin Yang Jianing Ye Chengjie Wu Ziqing Mai Yujing Hu Tangjie Lv Changjie Fan Qianchuan Zhao Chongjie Zhang OffRL OnRL 195 7 0 31 May 2024
Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation Jianliang He Han Zhong Zhuoran Yang 183 6 0 19 Apr 2024
Regret Minimization via Saddle Point OptimizationNeural Information Processing Systems (NeurIPS), 2024 Johannes Kirschner Seyed Alireza Bakhtiari Kushagra Chandak Volodymyr Tkachuk Csaba Szepesvári 144 2 0 15 Mar 2024
Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent Yingru Li Jiawei Xu Lei Han Zhi-Quan Luo BDL OffRL 242 7 0 05 Feb 2024
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling, and Beyond Thanh Nguyen-Tang Raman Arora OffRL 226 5 0 06 Jan 2024
Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation Jiayi Huang Han Zhong Liwei Wang Lin F. Yang 147 3 0 07 Dec 2023
Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2023 Ahmadreza Moradipari M. Pedramfar Modjtaba Shokrian Zini Vaneet Aggarwal 261 6 0 30 Oct 2023
Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement LearningInternational Conference on Learning Representations (ICLR), 2023 Mirco Mutti Ric De Santi Marcello Restelli Alexander Marx Giorgia Ramponi CML 236 5 0 11 Oct 2023
Sample-Efficient Multi-Agent RL: An Optimization PerspectiveInternational Conference on Learning Representations (ICLR), 2023 Nuoya Xiong Zhihan Liu Zhaoran Wang Zhuoran Yang 231 1 0 10 Oct 2023
Maximize to Explore: One Objective Function Fusing Estimation, Planning, and ExplorationNeural Information Processing Systems (NeurIPS), 2023 Zhihan Liu Miao Lu Wei Xiong Han Zhong Haotian Hu Shenao Zhang Sirui Zheng Zhuoran Yang Zhaoran Wang OffRL 312 24 0 29 May 2023
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte CarloInternational Conference on Learning Representations (ICLR), 2023 Haque Ishfaq Qingfeng Lan Pan Xu A. R. Mahmood Doina Precup Anima Anandkumar Kamyar Azizzadenesheli BDL OffRL 252 27 0 29 May 2023
The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2023 Kaiwen Wang Kevin Zhou Runzhe Wu Nathan Kallus Wen Sun OffRL 402 23 0 25 May 2023
Bridging Imitation and Online Reinforcement Learning: An Optimistic Tale Botao Hao Rahul Jain Dengwang Tang Zheng Wen OffRL 158 5 0 20 Mar 2023
Eluder-based Regret for Stochastic Contextual MDPsInternational Conference on Machine Learning (ICML), 2022 Orin Levy Asaf B. Cassel Alon Cohen Yishay Mansour 230 7 0 27 Nov 2022
Model-Free Reinforcement Learning with the Decision-Estimation CoefficientNeural Information Processing Systems (NeurIPS), 2022 Dylan J. Foster Noah Golowich Jian Qian Alexander Rakhlin Ayush Sekhari OffRL 189 12 0 25 Nov 2022
A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov GamesInternational Conference on Machine Learning (ICML), 2022 Wei Xiong Han Zhong Chengshuai Shi Cong Shen Tong Zhang 156 21 0 04 Oct 2022
Guarantees for Epsilon-Greedy Reinforcement Learning with Function ApproximationInternational Conference on Machine Learning (ICML), 2022 Christoph Dann Yishay Mansour M. Mohri Ayush Sekhari Karthik Sridharan 206 67 0 19 Jun 2022
Regret Bounds for Information-Directed Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2022 Botao Hao Tor Lattimore OffRL 234 23 0 09 Jun 2022
Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-efficiency of Posterior SamplingAnnual Conference Computational Learning Theory (COLT), 2022 Alekh Agarwal Tong Zhang 147 9 0 15 Mar 2022
Fast Rates in Pool-Based Batch Active Learning Claudio Gentile Zhilei Wang Tong Zhang 259 18 0 11 Feb 2022
Nonstationary Reinforcement Learning with Linear Function Approximation Huozhi Zhou Jinglin Chen Lav Varshney A. Jagmohan 299 31 0 08 Oct 2020