Why is Posterior Sampling Better than Optimism for Reinforcement Learning?

1 July 2016

Papers citing "Why is Posterior Sampling Better than Optimism for Reinforcement Learning?"

50 / 61 papers shown

Title
Toward Efficient Exploration by Large Language Model Agents Dilip Arumugam Thomas L. Griffiths LLMAG 92 1 0 29 Apr 2025
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model Moritz A. Zanger Pascal R. van der Vaart Wendelin Bohmer M. Spaan UQCV BDL 149 0 0 14 Mar 2025
Do ImageNet-trained models learn shortcuts? The impact of frequency shortcuts on generalization Shunxin Wang Raymond N. J. Veldhuis N. Strisciuglio VLM 71 0 0 05 Mar 2025
EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Siddharth Aravindan Dixant Mittal Wee Sun Lee BDL 79 0 0 17 Jan 2025
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling Jasmine Bayrooti Carl Henrik Ek Amanda Prorok 42 0 0 07 Oct 2024
NeoRL: Efficient Exploration for Nonepisodic RL Bhavya Sukhija Lenart Treven Florian Dorfler Stelian Coros Andreas Krause OffRL 30 0 0 03 Jun 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
Posterior Sampling-based Online Learning for Episodic POMDPs Dengwang Tang Dongze Ye Rahul Jain A. Nayyar Pierluigi Nuzzo OffRL 51 0 0 16 Oct 2023
Provably Efficient Exploration in Constrained Reinforcement Learning:Posterior Sampling Is All You Need Danil Provodin Pratik Gajane Mykola Pechenizkiy M. Kaptein 33 0 0 27 Sep 2023
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo Haque Ishfaq Qingfeng Lan Pan Xu A. R. Mahmood Doina Precup Anima Anandkumar Kamyar Azizzadenesheli BDL OffRL 28 20 0 29 May 2023
Bayesian Reinforcement Learning with Limited Cognitive Load Dilip Arumugam Mark K. Ho Noah D. Goodman Benjamin Van Roy OffRL 34 8 0 05 May 2023
Sharp Deviations Bounds for Dirichlet Weighted Sums with Application to analysis of Bayesian algorithms Denis Belomestny Pierre Menard A. Naumov D. Tiapkin Michal Valko 22 2 0 06 Apr 2023
Model-Based Uncertainty in Value Functions Carlos E. Luis A. Bottero Julia Vinogradska Felix Berkenkamp Jan Peters 36 13 0 24 Feb 2023
Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments Runlong Zhou Zihan Zhang S. Du 44 10 0 31 Jan 2023
STEERING: Stein Information Directed Exploration for Model-Based Reinforcement Learning Souradip Chakraborty Amrit Singh Bedi Alec Koppel Mengdi Wang Furong Huang Dinesh Manocha 24 7 0 28 Jan 2023
CIM: Constrained Intrinsic Motivation for Sparse-Reward Continuous Control Xiang Zheng Xingjun Ma Cong Wang 28 1 0 28 Nov 2022
On Rate-Distortion Theory in Capacity-Limited Cognition & Reinforcement Learning Dilip Arumugam Mark K. Ho Noah D. Goodman Benjamin Van Roy 28 4 0 30 Oct 2022
Planning to the Information Horizon of BAMDPs via Epistemic State Abstraction Dilip Arumugam Satinder Singh 24 3 0 30 Oct 2022
Opportunistic Episodic Reinforcement Learning Xiaoxiao Wang Nader Bouacida Xueying Guo Xin Liu 14 0 0 24 Oct 2022
On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness Haotian Ye Xiaoyu Chen Liwei Wang S. Du OffRL 24 6 0 19 Oct 2022
Square-root regret bounds for continuous-time episodic Markov decision processes Xuefeng Gao X. Zhou 43 6 0 03 Oct 2022
Ensemble Reinforcement Learning in Continuous Spaces -- A Hierarchical Multi-Step Approach for Policy Training Gang Chen Victoria Huang OffRL 31 0 0 29 Sep 2022
POEM: Out-of-Distribution Detection with Posterior Sampling Yifei Ming Ying Fan Yixuan Li OODD 29 113 0 28 Jun 2022
Between Rate-Distortion Theory & Value Equivalence in Model-Based Reinforcement Learning Dilip Arumugam Benjamin Van Roy OffRL 35 1 0 04 Jun 2022
Exploration in Deep Reinforcement Learning: A Survey Pawel Ladosz Lilian Weng Minwoo Kim H. Oh OffRL 23 324 0 02 May 2022
Horizon-Free Reinforcement Learning in Polynomial Time: the Power of Stationary Policies Zihan Zhang Xiangyang Ji S. Du 28 21 0 24 Mar 2022
Online Learning of Energy Consumption for Navigation of Electric Vehicles Niklas Åkerblom Yuxin Chen M. Chehreghani 20 12 0 03 Nov 2021
Settling the Horizon-Dependence of Sample Complexity in Reinforcement Learning Yuanzhi Li Ruosong Wang Lin F. Yang 17 20 0 01 Nov 2021
Reinforcement Learning in Reward-Mixing MDPs Jeongyeol Kwon Yonathan Efroni C. Caramanis Shie Mannor 30 15 0 07 Oct 2021
Feel-Good Thompson Sampling for Contextual Bandits and Reinforcement Learning Tong Zhang 22 63 0 02 Oct 2021
Greedy UnMixing for Q-Learning in Multi-Agent Reinforcement Learning Chapman Siu Jason M. Traish R. Xu 25 2 0 19 Sep 2021
A Survey of Exploration Methods in Reinforcement Learning Susan Amin Maziar Gomrokchi Harsh Satija H. V. Hoof Doina Precup OffRL 21 80 0 01 Sep 2021
Bayesian decision-making under misspecified priors with applications to meta-learning Max Simchowitz Christopher Tosh A. Krishnamurthy Daniel J. Hsu Thodoris Lykouris Miroslav Dudík Robert Schapire 17 49 0 03 Jul 2021
On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control Amrit Singh Bedi Anjaly Parayil Junyu Zhang Mengdi Wang Alec Koppel 30 15 0 15 Jun 2021
Reinforcement Learning, Bit by Bit Xiuyuan Lu Benjamin Van Roy Vikranth Dwaracherla M. Ibrahimi Ian Osband Zheng Wen 30 70 0 06 Mar 2021
Adaptive Transmission Scheduling in Wireless Networks for Asynchronous Federated Learning Hyun-Suk Lee Jang-Won Lee 81 53 0 02 Mar 2021
COMBO: Conservative Offline Model-Based Policy Optimization Tianhe Yu Aviral Kumar Rafael Rafailov Aravind Rajeswaran Sergey Levine Chelsea Finn OffRL 219 413 0 16 Feb 2021
Model-based Reinforcement Learning for Continuous Control with Posterior Sampling Ying Fan Yifei Ming 25 17 0 20 Nov 2020
Restless-UCB, an Efficient and Low-complexity Algorithm for Online Restless Bandits Siwei Wang Longbo Huang John C. S. Lui OffRL 16 38 0 05 Nov 2020
Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration Priyank Agrawal Jinglin Chen Nan Jiang 27 18 0 23 Oct 2020
Randomized Value Functions via Posterior State-Abstraction Sampling Dilip Arumugam Benjamin Van Roy OffRL 28 7 0 05 Oct 2020
An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles Niklas Åkerblom Yuxin Chen M. Chehreghani 16 15 0 03 Mar 2020
Concentration Inequalities for Multinoulli Random Variables Jian Qian Ronan Fruit Matteo Pirotta A. Lazaric 11 21 0 30 Jan 2020
Making Sense of Reinforcement Learning and Probabilistic Inference Brendan O'Donoghue Ian Osband Catalin Ionescu OffRL 22 47 0 03 Jan 2020
Convergence Rates of Posterior Distributions in Markov Decision Process Zhen Li E. Laber 13 0 0 22 Jul 2019
Regret Minimization for Reinforcement Learning by Evaluating the Optimal Bias Function Zihan Zhang Xiangyang Ji 11 71 0 12 Jun 2019
Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies Yonathan Efroni Nadav Merlis Mohammad Ghavamzadeh Shie Mannor OffRL 22 67 0 27 May 2019
A Bayesian Approach to Robust Reinforcement Learning E. Derman D. Mankowitz Timothy A. Mann Shie Mannor 18 57 0 20 May 2019
Meta reinforcement learning as task inference Jan Humplik Alexandre Galashov Leonard Hasenclever Pedro A. Ortega Yee Whye Teh N. Heess OffRL 29 127 0 15 May 2019
A Short Survey on Probabilistic Reinforcement Learning R. Russel 13 2 0 21 Jan 2019