Offline Reinforcement Learning

March 17, 2022

Semi-Markov Offline Reinforcement Learning for Healthcare
Mehdi Fatemi, Mary Wu, Jeremy Petch, Walter Nelson, Stuart J. Connolly, Alexander Benz, Anthony Carnicelli, Marzyeh Ghassemi
Reinforcement Learning Markov Decision Process Offline Reinforcement Learning Optimal Policy Healthcare System Offline Reinforcement Learning Algorithm

March 16, 2022

Latent-Variable Advantage-Weighted Policy Optimization for Offline RL
Xi Chen, Ali Ghadirzadeh, Tianhe Yu, Yuan Gao, Jianhao Wang, Wenzhe Li, Bin Liang, Chelsea Finn, Chongjie Zhang
Offline Reinforcement Learning Latent Action Policy Distribution
COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks
Fan Wu, Linyi Li, Chejian Xu, Huan Zhang, Bhavya Kailkhura, Krishnaram Kenthapadi, Ding Zhao, Bo Li
Reinforcement Learning Offline Reinforcement Learning Poisoning Attack Robust Policy Action Repetition Intrinsic Robustness Decentralized Aggregation

March 14, 2022

The Efficacy of Pessimism in Asynchronous Q-Learning
Yuling Yan, Gen Li, Yuxin Chen, Jianqing Fan
Offline Reinforcement Learning Q Learning State Action Pair Asynchronous Q Learning

March 13, 2022

DARA: Dynamics-Aware Reward Augmentation in Offline Reinforcement Learning
Jinxin Liu, Hongyin Zhang, Donglin Wang
Offline Reinforcement Learning Reward Function Offline Deep Reinforcement Learning

March 11, 2022

Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism
Ming Yin, Yaqi Duan, Mengdi Wang, Yu-Xiang Wang
Offline Reinforcement Learning Value Iteration Variance Information Linear Representation Offline Learning

March 3, 2022

Testing Stationarity and Change Point Detection in Reinforcement Learning
Mengbing Li, Chengchun Shi, Zhenke Wu, Piotr Fryzlewicz
Reinforcement Learning Offline Reinforcement Learning Change Point Detection Non Stationarity Nonstationary Environment Testing Stationarity

March 2, 2022

February 28, 2022

Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity
Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi
Reinforcement Learning Offline Reinforcement Learning Sample Complexity Q Learning Finite Horizon Near Optimal Policy

February 26, 2022

Statistically Efficient Advantage Learning for Offline Reinforcement Learning in Infinite Horizons
Chengchun Shi, Shikai Luo, Yuan Le, Hongtu Zhu, Rui Song
Reinforcement Learning Offline Reinforcement Learning Policy OpTimization Policy Optimization New Horizon Function Estimation Advantage Learning

February 23, 2022

Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning
Chenjia Bai, Lingxiao Wang, Zhuoran Yang, Zhihong Deng, Animesh Garg, Peng Liu, Zhaoran Wang
Offline Reinforcement Learning Bootstrapping End to End Linear MDPs Policy Algorithm Robust Offline Reinforcement Learning

February 19, 2022

A Behavior Regularized Implicit Policy for Offline Reinforcement Learning
Shentao Yang, Zhendong Wang, Huangjie Zheng, Yihao Feng, Mingyuan Zhou
Offline Reinforcement Learning BEHAVIOR Explanation State Action Pair Policy Based Reinforcement Learning Implicit Policy

February 17, 2022

Retrieval-Augmented Reinforcement Learning
Anirudh Goyal, Abram L. Friesen, Andrea Banino, Theophane Weber, Nan Rosemary Ke, Adria Puigdomenech Badia, Arthur Guez, Mehdi Mirza, Peter C. Humphreys, Ksenia Konyushkova, Laurent Sifre, Michal Valko, Simon Osindero, Timothy Lillicrap, Nicolas Heess, Charles Blundell
Deep Reinforcement Learning Offline Reinforcement Learning DQN Agent Policy Parameterization

February 13, 2022

Supported Policy Optimization for Offline Reinforcement Learning
Jialong Wu, Haixu Wu, Zihan Qiu, Jianmin Wang, Mingsheng Long
Reinforcement Learning Offline Reinforcement Learning Policy OpTimization Policy Reinforcement Learning Constrained Policy Optimization Support Estimation

February 11, 2022

Online Decision Transformer
Qinqing Zheng, Amy Zhang, Aditya Grover
Offline Reinforcement Learning Decision Transformer Sequence Modeling

February 10, 2022

Settling the Communication Complexity for Distributed Offline Reinforcement Learning
Juliusz Krysztof Ziomek, Jun Wang, Yaodong Yang
Offline Reinforcement Learning Contextual Bandit Offline Reinforcement Learning Algorithm Communication Complexity Episodic Markov Decision Process Minimax Rate

February 9, 2022

Offline Reinforcement Learning

Papers

Semi-Markov Offline Reinforcement Learning for Healthcare

Latent-Variable Advantage-Weighted Policy Optimization for Offline RL

COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks

The Efficacy of Pessimism in Asynchronous Q-Learning

DARA: Dynamics-Aware Reward Augmentation in Offline Reinforcement Learning

Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism

Testing Stationarity and Change Point Detection in Reinforcement Learning

A Survey on Offline Reinforcement Learning: Taxonomy, Review, and Open Problems

Reliable validation of Reinforcement Learning Benchmarks

Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity

Statistically Efficient Advantage Learning for Offline Reinforcement Learning in Infinite Horizons

Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning

A Behavior Regularized Implicit Policy for Offline Reinforcement Learning

Retrieval-Augmented Reinforcement Learning

Supported Policy Optimization for Offline Reinforcement Learning

Online Decision Transformer

Settling the Communication Complexity for Distributed Offline Reinforcement Learning

Bayesian Nonparametrics for Offline Skill Discovery

Offline Reinforcement Learning with Realizability and Single-policy Concentrability

Rethinking Goal-conditioned Supervised Learning and Its Connection to Offline RL