Is Reinforcement Learning More Difficult Than Bandits? A Near-optimal Algorithm Escaping the Curse of Horizon

28 September 2020

Papers citing "Is Reinforcement Learning More Difficult Than Bandits? A Near-optimal Algorithm Escaping the Curse of Horizon"

50 / 82 papers shown

Title
Sample and Computationally Efficient Continuous-Time Reinforcement Learning with General Function Approximation Runze Zhao Yue Yu Adams Yiyue Zhu Chen Yang Dongruo Zhou 7 0 0 20 May 2025
When a Reinforcement Learning Agent Encounters Unknown Unknowns Juntian Zhu Miguel de Carvalho Zhouwang Yang Fengxiang He 7 0 0 19 May 2025
Minimax Optimal Reinforcement Learning with Quasi-Optimism Harin Lee Min-hwan Oh OffRL 64 1 0 02 Mar 2025
Hybrid Transfer Reinforcement Learning: Provable Sample Efficiency from Shifted-Dynamics Data Chengrui Qu Laixi Shi Kishan Panaganti Pengcheng You Adam Wierman OffRL OnRL 38 0 0 06 Nov 2024
Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs Davide Maran Alberto Maria Metelli Matteo Papini Marcello Restelli 39 0 0 31 Oct 2024
Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents Safwan Labbi D. Tiapkin Lorenzo Mancini Paul Mangold Eric Moulines FedML 73 0 0 30 Oct 2024
Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition Zhong Zheng Haochen Zhang Lingzhou Xue OffRL 78 2 0 10 Oct 2024
State-free Reinforcement Learning Mingyu Chen Aldo Pacchiano Xuezhou Zhang 68 0 0 27 Sep 2024
Efficient Reinforcement Learning in Probabilistic Reward Machines Xiaofeng Lin Xuezhou Zhang 56 0 0 19 Aug 2024
Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization D. Tiapkin Evgenii Chzhen Gilles Stoltz 74 1 0 08 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
On Bits and Bandits: Quantifying the Regret-Information Trade-off Itai Shufaro Nadav Merlis Nir Weinberger Shie Mannor 38 0 0 26 May 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 79 6 0 04 Apr 2024
Utilizing Maximum Mean Discrepancy Barycenter for Propagating the Uncertainty of Value Functions in Reinforcement Learning Srinjoy Roy Swagatam Das 32 0 0 31 Mar 2024
The Value of Reward Lookahead in Reinforcement Learning Nadav Merlis Dorian Baudry Vianney Perchet 34 0 0 18 Mar 2024
Horizon-Free Regret for Linear Markov Decision Processes Zihan Zhang Jason D. Lee Yuxin Chen Simon S. Du 33 3 0 15 Mar 2024
Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks Ziping Xu Zifan Xu Runxuan Jiang Peter Stone Ambuj Tewari 48 1 0 03 Mar 2024
Rethinking Model-based, Policy-based, and Value-based Reinforcement Learning via the Lens of Representation Complexity Guhao Feng Han Zhong OffRL 76 2 0 28 Dec 2023
Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation Jiayi Huang Han Zhong Liwei Wang Lin F. Yang 39 2 0 07 Dec 2023
When is Agnostic Reinforcement Learning Statistically Tractable? Zeyu Jia Gene Li Alexander Rakhlin Ayush Sekhari Nathan Srebro OffRL 32 5 0 09 Oct 2023
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning Qiwei Di Heyang Zhao Jiafan He Quanquan Gu OffRL 61 5 0 02 Oct 2023
Settling the Sample Complexity of Online Reinforcement Learning Zihan Zhang Yuxin Chen Jason D. Lee S. Du OffRL 98 22 0 25 Jul 2023
Efficient Action Robust Reinforcement Learning with Probabilistic Policy Execution Uncertainty Guanin Liu Zhihan Zhou Han Liu Lifeng Lai 36 1 0 15 Jul 2023
Active Coverage for PAC Reinforcement Learning Aymen Al Marjani Andrea Tirinzoni E. Kaufmann OffRL 21 4 0 23 Jun 2023
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs Kaixuan Ji Qingyue Zhao Jiafan He Weitong Zhang Q. Gu 55 4 0 15 May 2023
Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs Junkai Zhang Weitong Zhang Quanquan Gu 33 3 0 17 Mar 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
A Reduction-based Framework for Sequential Decision Making with Delayed Feedback Yunchang Yang Hangshi Zhong Tianhao Wu B. Liu Liwei Wang S. Du OffRL 27 8 0 03 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
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
Beyond the Best: Estimating Distribution Functionals in Infinite-Armed Bandits Yifei Wang Tavor Z. Baharav Yanjun Han Jiantao Jiao David Tse 11 1 0 01 Nov 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
On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness Haotian Ye Xiaoyu Chen Liwei Wang S. Du OffRL 37 6 0 19 Oct 2022
A Unified Algorithm for Stochastic Path Problems Christoph Dann Chen-Yu Wei Julian Zimmert 35 0 0 17 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
Reaching Goals is Hard: Settling the Sample Complexity of the Stochastic Shortest Path Liyu Chen Andrea Tirinzoni Matteo Pirotta A. Lazaric 31 3 0 10 Oct 2022
The Role of Coverage in Online Reinforcement Learning Tengyang Xie Dylan J. Foster Yu Bai Nan Jiang Sham Kakade OffRL 38 57 0 09 Oct 2022
Sampling Through the Lens of Sequential Decision Making J. Dou Alvin Pan Runxue Bao Haiyi Mao Lei Luo Zhi-Hong Mao 26 19 0 17 Aug 2022
Instance-Dependent Near-Optimal Policy Identification in Linear MDPs via Online Experiment Design Andrew Wagenmaker Kevin G. Jamieson OffRL 32 25 0 06 Jul 2022
Near-Optimal Goal-Oriented Reinforcement Learning in Non-Stationary Environments Liyu Chen Haipeng Luo 35 8 0 25 May 2022
Computationally Efficient Horizon-Free Reinforcement Learning for Linear Mixture MDPs Dongruo Zhou Quanquan Gu 81 44 0 23 May 2022
Slowly Changing Adversarial Bandit Algorithms are Efficient for Discounted MDPs Ian A. Kash L. Reyzin Zishun Yu 31 0 0 18 May 2022
Provably Efficient Kernelized Q-Learning Shuang Liu H. Su MLT 27 4 0 21 Apr 2022
When Should We Prefer Offline Reinforcement Learning Over Behavioral Cloning? Aviral Kumar Joey Hong Anika Singh Sergey Levine OffRL 45 77 0 12 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
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity Laixi Shi Gen Li Yuting Wei Yuxin Chen Yuejie Chi OffRL 38 90 0 28 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
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
Improved No-Regret Algorithms for Stochastic Shortest Path with Linear MDP Liyu Chen Rahul Jain Haipeng Luo 43 14 0 18 Dec 2021