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
First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach Andrew Wagenmaker Yifang Chen Max Simchowitz S. Du Kevin G. Jamieson 73 37 0 07 Dec 2021
Dueling RL: Reinforcement Learning with Trajectory Preferences Aldo Pacchiano Aadirupa Saha Jonathan Lee 38 82 0 08 Nov 2021
Settling the Horizon-Dependence of Sample Complexity in Reinforcement Learning Yuanzhi Li Ruosong Wang Lin F. Yang 27 20 0 01 Nov 2021
Adaptive Discretization in Online Reinforcement Learning Sean R. Sinclair Siddhartha Banerjee Chao Yu OffRL 45 15 0 29 Oct 2021
Can Q-Learning be Improved with Advice? Noah Golowich Ankur Moitra OffRL 19 12 0 25 Oct 2021
Provable Hierarchy-Based Meta-Reinforcement Learning Kurtland Chua Qi Lei Jason D. Lee 22 5 0 18 Oct 2021
Towards Instance-Optimal Offline Reinforcement Learning with Pessimism Ming Yin Yu Wang OffRL 29 82 0 17 Oct 2021
Reward-Free Model-Based Reinforcement Learning with Linear Function Approximation Weitong Zhang Dongruo Zhou Quanquan Gu OffRL 30 27 0 12 Oct 2021
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning Gen Li Laixi Shi Yuxin Chen Yuejie Chi OffRL 49 51 0 09 Oct 2021
Theoretically Principled Deep RL Acceleration via Nearest Neighbor Function Approximation Junhong Shen Lin F. Yang OffRL 19 15 0 09 Oct 2021
Reinforcement Learning in Reward-Mixing MDPs Jeongyeol Kwon Yonathan Efroni Constantine Caramanis Shie Mannor 32 15 0 07 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 26 2 0 07 Oct 2021
A Bayesian Learning Algorithm for Unknown Zero-sum Stochastic Games with an Arbitrary Opponent Mehdi Jafarnia-Jahromi Rahul Jain A. Nayyar 41 5 0 08 Sep 2021
Gap-Dependent Unsupervised Exploration for Reinforcement Learning Jingfeng Wu Vladimir Braverman Lin F. Yang 33 12 0 11 Aug 2021
Beyond No Regret: Instance-Dependent PAC Reinforcement Learning Andrew Wagenmaker Max Simchowitz Kevin G. Jamieson 28 34 0 05 Aug 2021
Towards General Function Approximation in Zero-Sum Markov Games Baihe Huang Jason D. Lee Zhaoran Wang Zhuoran Yang 33 47 0 30 Jul 2021
Provably Efficient Multi-Task Reinforcement Learning with Model Transfer Chicheng Zhang Zhi Wang OffRL 27 19 0 19 Jul 2021
Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses Haipeng Luo Chen-Yu Wei Chung-Wei Lee 38 44 0 18 Jul 2021
Going Beyond Linear RL: Sample Efficient Neural Function Approximation Baihe Huang Kaixuan Huang Sham Kakade Jason D. Lee Qi Lei Runzhe Wang Jiaqi Yang 46 8 0 14 Jul 2021
Deep Learning for Embodied Vision Navigation: A Survey Fengda Zhu Yi Zhu Vincent CS Lee Xiaodan Liang Xiaojun Chang EgoV LM&Ro 44 0 0 07 Jul 2021
Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning Christoph Dann T. V. Marinov M. Mohri Julian Zimmert OffRL 11 29 0 02 Jul 2021
Instance-optimality in optimal value estimation: Adaptivity via variance-reduced Q-learning K. Khamaru Eric Xia Martin J. Wainwright Michael I. Jordan OffRL 36 20 0 28 Jun 2021
A Fully Problem-Dependent Regret Lower Bound for Finite-Horizon MDPs Andrea Tirinzoni Matteo Pirotta A. Lazaric 27 16 0 24 Jun 2021
A Reduction-Based Framework for Conservative Bandits and Reinforcement Learning Yunchang Yang Tianhao Wu Han Zhong Evrard Garcelon Matteo Pirotta A. Lazaric Liwei Wang S. Du OffRL 35 9 0 22 Jun 2021
Uniform-PAC Bounds for Reinforcement Learning with Linear Function Approximation Jiafan He Dongruo Zhou Quanquan Gu 27 12 0 22 Jun 2021
MADE: Exploration via Maximizing Deviation from Explored Regions Tianjun Zhang Paria Rashidinejad Jiantao Jiao Yuandong Tian Joseph E. Gonzalez Stuart J. Russell OffRL 34 42 0 18 Jun 2021
Reinforcement Learning for Markovian Bandits: Is Posterior Sampling more Scalable than Optimism? Nicolas Gast B. Gaujal K. Khun 28 2 0 16 Jun 2021
Implicit Finite-Horizon Approximation and Efficient Optimal Algorithms for Stochastic Shortest Path Liyu Chen Mehdi Jafarnia-Jahromi R. Jain Haipeng Luo 24 25 0 15 Jun 2021
Online Sub-Sampling for Reinforcement Learning with General Function Approximation Dingwen Kong Ruslan Salakhutdinov Ruosong Wang Lin F. Yang OffRL 38 1 0 14 Jun 2021
The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces Chi Jin Qinghua Liu Tiancheng Yu 26 50 0 07 Jun 2021
On the Theory of Reinforcement Learning with Once-per-Episode Feedback Niladri S. Chatterji Aldo Pacchiano Peter L. Bartlett Michael I. Jordan OffRL 27 24 0 29 May 2021
Online Selection of Diverse Committees Virginie Do Jamal Atif J. Lang Nicolas Usunier 40 8 0 19 May 2021
Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret Jean Tarbouriech Runlong Zhou S. Du Matteo Pirotta M. Valko A. Lazaric 65 35 0 22 Apr 2021
Minimax Regret for Stochastic Shortest Path Alon Cohen Yonathan Efroni Yishay Mansour Aviv A. Rosenberg 33 28 0 24 Mar 2021
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation Andrea Zanette Ching-An Cheng Alekh Agarwal 34 53 0 24 Mar 2021
Reinforcement Learning with Algorithms from Probabilistic Structure Estimation J. Epperlein R. Overko Sergiy Zhuk Christopher K. King Djallel Bouneffouf Andrew Cullen Robert Shorten OffRL 24 7 0 15 Mar 2021
UCB Momentum Q-learning: Correcting the bias without forgetting Pierre Menard O. D. Domingues Xuedong Shang Michal Valko 79 41 0 01 Mar 2021
Online Learning for Unknown Partially Observable MDPs Mehdi Jafarnia-Jahromi Rahul Jain A. Nayyar 34 20 0 25 Feb 2021
Near-Optimal Randomized Exploration for Tabular Markov Decision Processes Zhihan Xiong Ruoqi Shen Qiwen Cui Maryam Fazel S. Du 29 7 0 19 Feb 2021
Online Apprenticeship Learning Lior Shani Tom Zahavy Shie Mannor OffRL 29 25 0 13 Feb 2021
Improved Corruption Robust Algorithms for Episodic Reinforcement Learning Yifang Chen S. Du Kevin G. Jamieson 24 22 0 13 Feb 2021
Finding the Stochastic Shortest Path with Low Regret: The Adversarial Cost and Unknown Transition Case Liyu Chen Haipeng Luo 33 30 0 10 Feb 2021
Fine-Grained Gap-Dependent Bounds for Tabular MDPs via Adaptive Multi-Step Bootstrap Haike Xu Tengyu Ma S. Du 19 42 0 09 Feb 2021
Confidence-Budget Matching for Sequential Budgeted Learning Yonathan Efroni Nadav Merlis Aadirupa Saha Shie Mannor 40 10 0 05 Feb 2021
Near-Optimal Offline Reinforcement Learning via Double Variance Reduction Ming Yin Yu Bai Yu Wang OffRL 20 65 0 02 Feb 2021
Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms Chi Jin Qinghua Liu Sobhan Miryoosefi OffRL 38 215 0 01 Feb 2021
Online Markov Decision Processes with Aggregate Bandit Feedback Alon Cohen Haim Kaplan Tomer Koren Yishay Mansour OffRL 6 8 0 31 Jan 2021
Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP Zihan Zhang Jiaqi Yang Xiangyang Ji S. Du 71 38 0 29 Jan 2021
A Provably Efficient Algorithm for Linear Markov Decision Process with Low Switching Cost Minbo Gao Tianle Xie S. Du Lin F. Yang 36 46 0 02 Jan 2021
Learning Adversarial Markov Decision Processes with Delayed Feedback Tal Lancewicki Aviv A. Rosenberg Yishay Mansour 43 32 0 29 Dec 2020