Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds

1 January 2019

Papers citing "Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds"

50 / 216 papers shown

Title
Variance-aware robust reinforcement learning with linear function approximation under heavy-tailed rewards Xiang Li Qiang Sun 29 8 0 09 Mar 2023
Provably Efficient Reinforcement Learning via Surprise Bound Hanlin Zhu Ruosong Wang Jason D. Lee OffRL 28 5 0 22 Feb 2023
Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret Han Zhong Jiachen Hu Yecheng Xue Tongyang Li Liwei Wang 26 5 0 21 Feb 2023
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency Heyang Zhao Jiafan He Dongruo Zhou Tong Zhang Quanquan Gu 42 27 0 21 Feb 2023
Near-Minimax-Optimal Risk-Sensitive Reinforcement Learning with CVaR Kaiwen Wang Nathan Kallus Wen Sun 107 18 0 07 Feb 2023
Selective Uncertainty Propagation in Offline RL Sanath Kumar Krishnamurthy Shrey Modi Tanmay Gangwani S. Katariya B. Kveton A. Rangi OffRL 61 0 0 01 Feb 2023
Learning in POMDPs is Sample-Efficient with Hindsight Observability Jonathan Lee Alekh Agarwal Christoph Dann Tong Zhang 34 19 0 31 Jan 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
Regret Bounds for Markov Decision Processes with Recursive Optimized Certainty Equivalents Wenkun Xu Xuefeng Gao X. He 28 10 0 30 Jan 2023
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes Jiafan He Heyang Zhao Dongruo Zhou Quanquan Gu OffRL 51 53 0 12 Dec 2022
Near-Optimal Differentially Private Reinforcement Learning Dan Qiao Yu-Xiang Wang 30 13 0 09 Dec 2022
Leveraging Offline Data in Online Reinforcement Learning Andrew Wagenmaker Aldo Pacchiano OffRL OnRL 35 38 0 09 Nov 2022
On Rate-Distortion Theory in Capacity-Limited Cognition & Reinforcement Learning Dilip Arumugam Mark K. Ho Noah D. Goodman Benjamin Van Roy 31 4 0 30 Oct 2022
Hardness in Markov Decision Processes: Theory and Practice Michelangelo Conserva Paulo E. Rauber 37 3 0 24 Oct 2022
Horizon-Free and Variance-Dependent Reinforcement Learning for Latent Markov Decision Processes Runlong Zhou Ruosong Wang S. Du 31 3 0 20 Oct 2022
Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity Abhishek Gupta Aldo Pacchiano Yuexiang Zhai Sham Kakade Sergey Levine OffRL 41 66 0 18 Oct 2022
A Unified Algorithm for Stochastic Path Problems Christoph Dann Chen-Yu Wei Julian Zimmert 35 0 0 17 Oct 2022
Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data Allen Nie Yannis Flet-Berliac Deon R. Jordan William Steenbergen Emma Brunskill OffRL 31 12 0 16 Oct 2022
Near-Optimal Regret Bounds for Multi-batch Reinforcement Learning Zihan Zhang Yuhang Jiang Yuanshuo Zhou Xiangyang Ji OffRL 26 9 0 15 Oct 2022
Square-root regret bounds for continuous-time episodic Markov decision processes Xuefeng Gao X. Zhou 43 6 0 03 Oct 2022
Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient Ming Yin Mengdi Wang Yu-Xiang Wang OffRL 77 12 0 03 Oct 2022
Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation Dan Qiao Yu-Xiang Wang OffRL 75 13 0 03 Oct 2022
A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning Zixiang Chen C. J. Li An Yuan Quanquan Gu Michael I. Jordan OffRL 116 26 0 30 Sep 2022
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees D. Tiapkin Denis Belomestny Daniele Calandriello Eric Moulines Rémi Munos A. Naumov Mark Rowland Michal Valko Pierre Menard 44 8 0 28 Sep 2022
Multi-armed Bandit Learning on a Graph Tianpeng Zhang Kasper Johansson Na Li 33 6 0 20 Sep 2022
Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions Shuang Qiu Xiaohan Wei Jieping Ye Zhaoran Wang Zhuoran Yang OffRL 30 11 0 25 Jul 2022
Optimistic PAC Reinforcement Learning: the Instance-Dependent View Andrea Tirinzoni Aymen Al Marjani E. Kaufmann 17 12 0 12 Jul 2022
Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation Pihe Hu Yu Chen Longbo Huang 11 34 0 23 Jun 2022
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity Alekh Agarwal Tong Zhang 47 22 0 15 Jun 2022
Offline Stochastic Shortest Path: Learning, Evaluation and Towards Optimality Ming Yin Wenjing Chen Mengdi Wang Yu-Xiang Wang OffRL 30 4 0 10 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 31 25 0 09 Jun 2022
Provably Efficient Risk-Sensitive Reinforcement Learning: Iterated CVaR and Worst Path Yihan Du Siwei Wang Longbo Huang OOD 24 13 0 06 Jun 2022
Asymptotic Instance-Optimal Algorithms for Interactive Decision Making Kefan Dong Tengyu Ma 23 9 0 06 Jun 2022
Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning Dilip Arumugam Benjamin Van Roy OffRL 38 15 0 04 Jun 2022
Stabilizing Q-learning with Linear Architectures for Provably Efficient Learning Andrea Zanette Martin J. Wainwright OOD 38 5 0 01 Jun 2022
On Gap-dependent Bounds for Offline Reinforcement Learning Xinqi Wang Qiwen Cui S. Du OffRL 71 12 0 01 Jun 2022
Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret Jiawei Huang Li Zhao Tao Qin Wei Chen Nan Jiang Tie-Yan Liu OffRL 24 3 0 25 May 2022
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses D. Tiapkin Denis Belomestny Eric Moulines A. Naumov S. Samsonov Yunhao Tang Michal Valko Pierre Menard 31 17 0 16 May 2022
Provably Efficient Kernelized Q-Learning Shuang Liu H. Su MLT 27 4 0 21 Apr 2022
Horizon-Free Reinforcement Learning in Polynomial Time: the Power of Stationary Policies Zihan Zhang Xiangyang Ji S. Du 30 21 0 24 Mar 2022
Bellman Residual Orthogonalization for Offline Reinforcement Learning Andrea Zanette Martin J. Wainwright OffRL 30 8 0 24 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 34 66 0 11 Mar 2022
Branching Reinforcement Learning Yihan Du Wei Chen 27 0 0 16 Feb 2022
Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality Jiawei Huang Jinglin Chen Li Zhao Tao Qin Nan Jiang Tie-Yan Liu OffRL 35 23 0 14 Feb 2022
Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost Dan Qiao Ming Yin Ming Min Yu-Xiang Wang 43 28 0 13 Feb 2022
Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes Andrew Wagenmaker Yifang Chen Max Simchowitz S. Du Kevin G. Jamieson 19 48 0 26 Jan 2022
Instance-Dependent Confidence and Early Stopping for Reinforcement Learning K. Khamaru Eric Xia Martin J. Wainwright Michael I. Jordan 37 5 0 21 Jan 2022
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee Tianhao Wu Yunchang Yang Han Zhong Liwei Wang S. Du Jiantao Jiao 55 14 0 21 Dec 2021
Differentially Private Regret Minimization in Episodic Markov Decision Processes Sayak Ray Chowdhury Xingyu Zhou 26 21 0 20 Dec 2021
Improved No-Regret Algorithms for Stochastic Shortest Path with Linear MDP Liyu Chen Rahul Jain Haipeng Luo 43 14 0 18 Dec 2021