Minimax Regret Bounds for Reinforcement Learning

16 March 2017

Papers citing "Minimax Regret Bounds for Reinforcement Learning"

50 / 241 papers shown

Title
Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization Fang-yuan Kong Xiangcheng Zhang Baoxiang Wang Shuai Li 36 12 0 14 Feb 2023
Robust Knowledge Transfer in Tiered Reinforcement Learning Jiawei Huang Niao He OffRL 43 1 0 10 Feb 2023
$Extragradient-Type Methods with $\mathcal{O} (1/k)$ Last-Iterate Convergence Rates for Co-Hypomonotone Inclusions$ Extragradient-Type Methods with $\mathcal{O} (1/k)$ Last-Iterate Convergence Rates for Co-Hypomonotone Inclusions Quoc Tran-Dinh 42 2 0 08 Feb 2023
Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation Qiwen Cui Kai Zhang S. Du 60 23 0 07 Feb 2023
Online Reinforcement Learning with Uncertain Episode Lengths Debmalya Mandal Goran Radanović Jiarui Gan Adish Singla R. Majumdar OffRL 41 5 0 07 Feb 2023
Near-Minimax-Optimal Risk-Sensitive Reinforcement Learning with CVaR Kaiwen Wang Nathan Kallus Wen Sun 114 18 0 07 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 50 8 0 03 Feb 2023
Sample Complexity of Kernel-Based Q-Learning Sing-Yuan Yeh Fu-Chieh Chang Chang-Wei Yueh Pei-Yuan Wu A. Bernacchia Sattar Vakili OffRL 49 4 0 01 Feb 2023
Learning in POMDPs is Sample-Efficient with Hindsight Observability Jonathan Lee Alekh Agarwal Christoph Dann Tong Zhang 39 20 0 31 Jan 2023
An Efficient Solution to s-Rectangular Robust Markov Decision Processes Navdeep Kumar Kfir Y. Levy Kaixin Wang Shie Mannor 36 2 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 49 10 0 31 Jan 2023
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation Uri Sherman Tomer Koren Yishay Mansour 55 12 0 30 Jan 2023
Understanding the Complexity Gains of Single-Task RL with a Curriculum Qiyang Li Yuexiang Zhai Yi-An Ma Sergey Levine 42 14 0 24 Dec 2022
Latent Variable Representation for Reinforcement Learning Tongzheng Ren Chenjun Xiao Tianjun Zhang Na Li Zhaoran Wang Sujay Sanghavi Dale Schuurmans Bo Dai OffRL 38 10 0 17 Dec 2022
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes Jiafan He Heyang Zhao Dongruo Zhou Quanquan Gu OffRL 74 55 0 12 Dec 2022
Data-pooling Reinforcement Learning for Personalized Healthcare Intervention Xinyun Chen P. Shi Shanwen Pu OffRL 35 4 0 16 Nov 2022
On Rate-Distortion Theory in Capacity-Limited Cognition & Reinforcement Learning Dilip Arumugam Mark K. Ho Noah D. Goodman Benjamin Van Roy 42 4 0 30 Oct 2022
Opportunistic Episodic Reinforcement Learning Xiaoxiao Wang Nader Bouacida Xueying Guo Xin Liu 24 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 37 6 0 19 Oct 2022
A Unified Algorithm for Stochastic Path Problems Christoph Dann Chen-Yu Wei Julian Zimmert 40 0 0 17 Oct 2022
Near-Optimal Regret Bounds for Multi-batch Reinforcement Learning Zihan Zhang Yuhang Jiang Yuanshuo Zhou Xiangyang Ji OffRL 31 9 0 15 Oct 2022
Regret Bounds for Risk-Sensitive Reinforcement Learning Osbert Bastani Y. Ma E. Shen Wei Xu 46 18 0 11 Oct 2022
Tractable Optimality in Episodic Latent MABs Jeongyeol Kwon Yonathan Efroni Constantine Caramanis Shie Mannor 60 3 0 05 Oct 2022
Reward-Mixing MDPs with a Few Latent Contexts are Learnable Jeongyeol Kwon Yonathan Efroni Constantine Caramanis Shie Mannor 38 5 0 05 Oct 2022
Square-root regret bounds for continuous-time episodic Markov decision processes Xuefeng Gao X. Zhou 63 6 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
Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms Fan Chen Yu Bai Song Mei 53 22 0 29 Sep 2022
Multi-armed Bandit Learning on a Graph Tianpeng Zhang Kasper Johansson Na Li 42 6 0 20 Sep 2022
On the Convergence of Monte Carlo UCB for Random-Length Episodic MDPs Zixuan Dong Che Wang Keith Ross 38 3 0 07 Sep 2022
Socially Fair Reinforcement Learning Debmalya Mandal Jiarui Gan OffRL 30 13 0 26 Aug 2022
Strategic Decision-Making in the Presence of Information Asymmetry: Provably Efficient RL with Algorithmic Instruments Mengxin Yu Zhuoran Yang Jianqing Fan OffRL 54 8 0 23 Aug 2022
Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model Gen Li Yuejie Chi Yuting Wei Yuxin Chen 40 18 0 22 Aug 2022
Spectral Decomposition Representation for Reinforcement Learning Tongzheng Ren Tianjun Zhang Lisa Lee Joseph E. Gonzalez Dale Schuurmans Bo Dai OffRL 49 27 0 19 Aug 2022
Making Linear MDPs Practical via Contrastive Representation Learning Tianjun Zhang Tongzheng Ren Mengjiao Yang Joseph E. Gonzalez Dale Schuurmans Bo Dai 30 44 0 14 Jul 2022
PAC Reinforcement Learning for Predictive State Representations Wenhao Zhan Masatoshi Uehara Wen Sun Jason D. Lee 42 38 0 12 Jul 2022
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity Alekh Agarwal Tong Zhang 59 22 0 15 Jun 2022
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Conservative Natural Policy Gradient Primal-Dual Algorithm Qinbo Bai Amrit Singh Bedi Vaneet Aggarwal 31 20 0 12 Jun 2022
Offline Stochastic Shortest Path: Learning, Evaluation and Towards Optimality Ming Yin Wenjing Chen Mengdi Wang Yu Wang OffRL 32 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 36 25 0 09 Jun 2022
Provably Efficient Risk-Sensitive Reinforcement Learning: Iterated CVaR and Worst Path Yihan Du Siwei Wang Longbo Huang OOD 39 13 0 06 Jun 2022
Sample-Efficient Reinforcement Learning of Partially Observable Markov Games Qinghua Liu Csaba Szepesvári Chi Jin 69 20 0 02 Jun 2022
Incrementality Bidding via Reinforcement Learning under Mixed and Delayed Rewards Ashwinkumar Badanidiyuru Zhe Feng Tianxi Li Haifeng Xu OffRL 48 3 0 02 Jun 2022
Offline Reinforcement Learning with Differential Privacy Dan Qiao Yu Wang OffRL 44 23 0 02 Jun 2022
Byzantine-Robust Online and Offline Distributed Reinforcement Learning Yiding Chen Xuezhou Zhang Kai Zhang Mengdi Wang Xiaojin Zhu OffRL 43 16 0 01 Jun 2022
Chain of Thought Imitation with Procedure Cloning Mengjiao Yang Dale Schuurmans Pieter Abbeel Ofir Nachum OffRL 40 30 0 22 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 36 17 0 16 May 2022
Provably Efficient Kernelized Q-Learning Shuang Liu H. Su MLT 46 4 0 21 Apr 2022
Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency Qi Cai Zhuoran Yang Zhaoran Wang 43 14 0 20 Apr 2022
When Is Partially Observable Reinforcement Learning Not Scary? Qinghua Liu Alan Chung Csaba Szepesvári Chi Jin 27 94 0 19 Apr 2022
The Complexity of Markov Equilibrium in Stochastic Games C. Daskalakis Noah Golowich Kai Zhang 41 56 0 08 Apr 2022