Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning

13 November 2019

Papers citing "Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning"

47 / 47 papers shown

Title
Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory Alexander Levine Peter Stone Amy Zhang OffRL 41 0 0 03 Oct 2024
The Central Role of the Loss Function in Reinforcement Learning Kaiwen Wang Nathan Kallus Wen Sun OffRL 56 7 0 19 Sep 2024
A Note on Loss Functions and Error Compounding in Model-based Reinforcement Learning Nan Jiang 22 5 0 15 Apr 2024
Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning Noah Golowich Ankur Moitra Dhruv Rohatgi OffRL 35 4 0 04 Apr 2024
When is Agnostic Reinforcement Learning Statistically Tractable? Zeyu Jia Gene Li Alexander Rakhlin Ayush Sekhari Nathan Srebro OffRL 27 5 0 09 Oct 2023
Policy Finetuning in Reinforcement Learning via Design of Experiments using Offline Data Ruiqi Zhang Andrea Zanette OffRL OnRL 40 7 0 10 Jul 2023
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP Jiacheng Guo Zihao Li Huazheng Wang Mengdi Wang Zhuoran Yang Xuezhou Zhang 32 5 0 21 Jun 2023
Accelerating exploration and representation learning with offline pre-training Bogdan Mazoure Jake Bruce Doina Precup Rob Fergus Ankit Anand OffRL 31 5 0 31 Mar 2023
Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs Yuan Cheng Ruiquan Huang J. Yang Yitao Liang OffRL 41 8 0 20 Mar 2023
Fast exploration and learning of latent graphs with aliased observations Miguel Lazaro-Gredilla Ishani Deshpande Siva K. Swaminathan Meet Dave Dileep George 23 3 0 13 Mar 2023
Distributional Offline Policy Evaluation with Predictive Error Guarantees Runzhe Wu Masatoshi Uehara Wen Sun OffRL 38 13 0 19 Feb 2023
Near-Minimax-Optimal Risk-Sensitive Reinforcement Learning with CVaR Kaiwen Wang Nathan Kallus Wen Sun 107 18 0 07 Feb 2023
Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning Riashat Islam Hongyu Zang Anirudh Goyal Alex Lamb Kenji Kawaguchi Xin-hui Li Romain Laroche Yoshua Bengio Rémi Tachet des Combes OffRL AI4CE 23 9 0 01 Nov 2022
Planning to the Information Horizon of BAMDPs via Epistemic State Abstraction Dilip Arumugam Satinder Singh 24 3 0 30 Oct 2022
Hardness in Markov Decision Processes: Theory and Practice Michelangelo Conserva Paulo E. Rauber 32 3 0 24 Oct 2022
Spectral Decomposition Representation for Reinforcement Learning Tongzheng Ren Tianjun Zhang Lisa Lee Joseph E. Gonzalez Dale Schuurmans Bo Dai OffRL 40 27 0 19 Aug 2022
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning Shuang Qiu Lingxiao Wang Chenjia Bai Zhuoran Yang Zhaoran Wang SSL OffRL 26 32 0 29 Jul 2022
Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models Alex Lamb Riashat Islam Yonathan Efroni Aniket Didolkar Dipendra Kumar Misra Dylan J. Foster Lekan Molu Rajan Chari A. Krishnamurthy John Langford 41 24 0 17 Jul 2022
Making Linear MDPs Practical via Contrastive Representation Learning Tianjun Zhang Tongzheng Ren Mengjiao Yang Joseph E. Gonzalez Dale Schuurmans Bo Dai 25 44 0 14 Jul 2022
Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems Masatoshi Uehara Ayush Sekhari Jason D. Lee Nathan Kallus Wen Sun OffRL 49 31 0 24 Jun 2022
On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL Jinglin Chen Aditya Modi A. Krishnamurthy Nan Jiang Alekh Agarwal 38 25 0 21 Jun 2022
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity Alekh Agarwal Tong Zhang 44 22 0 15 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 29 25 0 09 Jun 2022
Uniqueness and Complexity of Inverse MDP Models Marcus Hutter S. Hansen 17 4 0 02 Jun 2022
Provable Benefits of Representational Transfer in Reinforcement Learning Alekh Agarwal Yuda Song Wen Sun Kaiwen Wang Mengdi Wang Xuezhou Zhang OffRL 21 33 0 29 May 2022
Chemoreception and chemotaxis of a three-sphere swimmer S. Paz R. Ausas J. P. Carbajal G. Buscaglia 11 4 0 05 May 2022
When Is Partially Observable Reinforcement Learning Not Scary? Qinghua Liu Alan Chung Csaba Szepesvári Chi Jin 14 92 0 19 Apr 2022
Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning Approach Xuezhou Zhang Yuda Song Masatoshi Uehara Mengdi Wang Alekh Agarwal Wen Sun OffRL 24 57 0 31 Jan 2022
A Free Lunch from the Noise: Provable and Practical Exploration for Representation Learning Tongzheng Ren Tianjun Zhang Csaba Szepesvári Bo Dai 22 19 0 22 Nov 2021
Representation Learning for Online and Offline RL in Low-rank MDPs Masatoshi Uehara Xuezhou Zhang Wen Sun OffRL 53 126 0 09 Oct 2021
The Information Geometry of Unsupervised Reinforcement Learning Benjamin Eysenbach Ruslan Salakhutdinov Sergey Levine SSL OffRL 61 31 0 06 Oct 2021
Explore and Control with Adversarial Surprise Arnaud Fickinger Natasha Jaques Samyak Parajuli Michael Chang Nicholas Rhinehart Glen Berseth Stuart J. Russell Sergey Levine 32 8 0 12 Jul 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 30 15 0 15 Jun 2021
Which Mutual-Information Representation Learning Objectives are Sufficient for Control? Kate Rakelly Abhishek Gupta Carlos Florensa Sergey Levine SSL 26 38 0 14 Jun 2021
Learning Markov State Abstractions for Deep Reinforcement Learning Cameron Allen Neev Parikh Omer Gottesman George Konidaris BDL OffRL 29 35 0 08 Jun 2021
Rapid Exploration for Open-World Navigation with Latent Goal Models Dhruv Shah Benjamin Eysenbach G. Kahn Nicholas Rhinehart Sergey Levine 24 70 0 12 Apr 2021
An Exponential Lower Bound for Linearly-Realizable MDPs with Constant Suboptimality Gap Yuanhao Wang Ruosong Wang Sham Kakade OffRL 39 43 0 23 Mar 2021
Return-Based Contrastive Representation Learning for Reinforcement Learning Guoqing Liu Chuheng Zhang Li Zhao Tao Qin Jinhua Zhu Jian Li Nenghai Yu Tie-Yan Liu SSL OffRL 11 47 0 22 Feb 2021
Model-Invariant State Abstractions for Model-Based Reinforcement Learning Manan Tomar Amy Zhang Roberto Calandra Matthew E. Taylor Joelle Pineau 19 24 0 19 Feb 2021
Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP Zihan Zhang Jiaqi Yang Xiangyang Ji S. Du 71 36 0 29 Jan 2021
Randomized Value Functions via Posterior State-Abstraction Sampling Dilip Arumugam Benjamin Van Roy OffRL 28 7 0 05 Oct 2020
Contrastive learning, multi-view redundancy, and linear models Christopher Tosh A. Krishnamurthy Daniel J. Hsu SSL 8 163 0 24 Aug 2020
FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs Alekh Agarwal Sham Kakade A. Krishnamurthy Wen Sun OffRL 41 222 0 18 Jun 2020
$Q$ -learning with Logarithmic Regret Kunhe Yang Lin F. Yang S. Du 37 59 0 16 Jun 2020
Deep Reinforcement and InfoMax Learning Bogdan Mazoure Rémi Tachet des Combes T. Doan Philip Bachman R. Devon Hjelm AI4CE 25 108 0 12 Jun 2020
Towards Understanding Cooperative Multi-Agent Q-Learning with Value Factorization Jianhao Wang Zhizhou Ren Beining Han Jianing Ye Chongjie Zhang OffRL 21 32 0 31 May 2020
Reward-Free Exploration for Reinforcement Learning Chi Jin A. Krishnamurthy Max Simchowitz Tiancheng Yu OffRL 112 194 0 07 Feb 2020