Is Q-learning Provably Efficient?

10 July 2018

Papers citing "Is Q-learning Provably Efficient?"

50 / 225 papers shown

Title
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback Tiancheng Jin Tal Lancewicki Haipeng Luo Yishay Mansour Aviv A. Rosenberg 74 21 0 31 Jan 2022
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee Tianhao Wu Yunchang Yang Han Zhong Liwei Wang S. Du Jiantao Jiao 60 14 0 21 Dec 2021
Provable Hierarchical Lifelong Learning with a Sketch-based Modular Architecture Zihao Deng Zee Fryer Brendan Juba Rina Panigrahy Xin Wang 27 2 0 21 Dec 2021
Recent Advances in Reinforcement Learning in Finance B. Hambly Renyuan Xu Huining Yang OffRL 34 168 0 08 Dec 2021
Differentially Private Exploration in Reinforcement Learning with Linear Representation Paul Luyo Evrard Garcelon A. Lazaric Matteo Pirotta 60 11 0 02 Dec 2021
Interesting Object, Curious Agent: Learning Task-Agnostic Exploration Simone Parisi Victoria Dean Deepak Pathak Abhinav Gupta LM&Ro 44 50 0 25 Nov 2021
A Free Lunch from the Noise: Provable and Practical Exploration for Representation Learning Tongzheng Ren Tianjun Zhang Csaba Szepesvári Bo Dai 39 19 0 22 Nov 2021
Uncoupled Bandit Learning towards Rationalizability: Benchmarks, Barriers, and Algorithms Jibang Wu Haifeng Xu Fan Yao 42 1 0 10 Nov 2021
Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning Yingjie Fei Zhuoran Yang Yudong Chen Zhaoran Wang 55 47 0 06 Nov 2021
Perturbational Complexity by Distribution Mismatch: A Systematic Analysis of Reinforcement Learning in Reproducing Kernel Hilbert Space Jihao Long Jiequn Han 34 6 0 05 Nov 2021
Decentralized Cooperative Reinforcement Learning with Hierarchical Information Structure Hsu Kao Chen-Yu Wei V. Subramanian 36 12 0 01 Nov 2021
Settling the Horizon-Dependence of Sample Complexity in Reinforcement Learning Yuanzhi Li Ruosong Wang Lin F. Yang 32 20 0 01 Nov 2021
Adaptive Discretization in Online Reinforcement Learning Sean R. Sinclair Siddhartha Banerjee Chao Yu OffRL 47 15 0 29 Oct 2021
Learning Stochastic Shortest Path with Linear Function Approximation Steffen Czolbe Jiafan He Adrian Dalca Quanquan Gu 53 30 0 25 Oct 2021
Optimistic Policy Optimization is Provably Efficient in Non-stationary MDPs Han Zhong Zhuoran Yang Zhaoran Wang Csaba Szepesvári 49 21 0 18 Oct 2021
On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning Weichao Mao Lin F. Yang Kai Zhang Tamer Bacsar 46 57 0 12 Oct 2021
Provably Efficient Reinforcement Learning in Decentralized General-Sum Markov Games Weichao Mao Tamer Basar 39 66 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
Provably Efficient Black-Box Action Poisoning Attacks Against Reinforcement Learning Guanlin Liu Lifeng Lai AAML 32 34 0 09 Oct 2021
When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently? Ziang Song Song Mei Yu Bai 76 67 0 08 Oct 2021
Understanding Domain Randomization for Sim-to-real Transfer Xiaoyu Chen Jiachen Hu Chi Jin Lihong Li Liwei Wang 24 112 0 07 Oct 2021
Explaining Off-Policy Actor-Critic From A Bias-Variance Perspective Ting-Han Fan Peter J. Ramadge CML FAtt OffRL 21 2 0 06 Oct 2021
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain Jianye Hao Tianpei Yang Hongyao Tang Chenjia Bai Jinyi Liu Zhaopeng Meng Peng Liu Zhen Wang OffRL 41 94 0 14 Sep 2021
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach Qinbo Bai Amrit Singh Bedi Mridul Agarwal Alec Koppel Vaneet Aggarwal 107 56 0 13 Sep 2021
Concave Utility Reinforcement Learning with Zero-Constraint Violations Mridul Agarwal Qinbo Bai Vaneet Aggarwal 38 12 0 12 Sep 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
On the Complexity of Computing Markov Perfect Equilibrium in General-Sum Stochastic Games Xiaotie Deng Ningyuan Li D. Mguni Jun Wang Yaodong Yang 31 46 0 04 Sep 2021
A Survey of Exploration Methods in Reinforcement Learning Susan Amin Maziar Gomrokchi Harsh Satija H. V. Hoof Doina Precup OffRL 39 80 0 01 Sep 2021
Gap-Dependent Unsupervised Exploration for Reinforcement Learning Jingfeng Wu Vladimir Braverman Lin F. Yang 35 12 0 11 Aug 2021
Towards General Function Approximation in Zero-Sum Markov Games Baihe Huang Jason D. Lee Zhaoran Wang Zhuoran Yang 38 47 0 30 Jul 2021
Strategically Efficient Exploration in Competitive Multi-agent Reinforcement Learning R. Loftin Aadirupa Saha Sam Devlin Katja Hofmann 30 5 0 30 Jul 2021
Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses Haipeng Luo Chen-Yu Wei Chung-Wei Lee 43 44 0 18 Jul 2021
Sublinear Regret for Learning POMDPs Yi Xiong Ningyuan Chen Xuefeng Gao Xiang Zhou 33 25 0 08 Jul 2021
Concentration of Contractive Stochastic Approximation and Reinforcement Learning Siddharth Chandak Vivek Borkar Parth Dodhia 48 17 0 27 Jun 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 43 15 0 15 Jun 2021
Randomized Exploration for Reinforcement Learning with General Value Function Approximation Haque Ishfaq Qiwen Cui V. Nguyen Alex Ayoub Zhuoran Yang Zhaoran Wang Doina Precup Lin F. Yang 40 43 0 15 Jun 2021
Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning Tengyang Xie Nan Jiang Huan Wang Caiming Xiong Yu Bai OffRL OnRL 44 162 0 09 Jun 2021
The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition Tiancheng Jin Longbo Huang Haipeng Luo 27 40 0 08 Jun 2021
The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces Chi Jin Qinghua Liu Tiancheng Yu 31 50 0 07 Jun 2021
Heuristic-Guided Reinforcement Learning Ching-An Cheng Andrey Kolobov Adith Swaminathan OffRL 40 61 0 05 Jun 2021
A Provably-Efficient Model-Free Algorithm for Constrained Markov Decision Processes Honghao Wei Xin Liu Lei Ying 32 21 0 03 Jun 2021
Sublinear Least-Squares Value Iteration via Locality Sensitive Hashing Anshumali Shrivastava Zhao Song Zhaozhuo Xu 24 22 0 18 May 2021
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting Gen Li Yuxin Chen Yuejie Chi Yuantao Gu Yuting Wei OffRL 37 28 0 17 May 2021
Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings Ming Yin Yu Wang OffRL 39 19 0 13 May 2021
Principled Exploration via Optimistic Bootstrapping and Backward Induction Chenjia Bai Lingxiao Wang Lei Han Jianye Hao Animesh Garg Peng Liu Zhaoran Wang OffRL 31 38 0 13 May 2021
Model-based Multi-agent Policy Optimization with Adaptive Opponent-wise Rollouts Weinan Zhang Xihuai Wang Jian Shen Ming Zhou 30 35 0 07 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 70 35 0 22 Apr 2021
Nearly Horizon-Free Offline Reinforcement Learning Tongzheng Ren Jialian Li Bo Dai S. Du Sujay Sanghavi OffRL 32 49 0 25 Mar 2021
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation Andrea Zanette Ching-An Cheng Alekh Agarwal 37 53 0 24 Mar 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