Robust Policy

Robust policy learning in reinforcement learning (RL) focuses on developing agents capable of performing well despite uncertainties and disturbances in their environment, a crucial step for deploying RL in real-world settings. Current research emphasizes techniques like adversarial training, curriculum learning, and the use of factored state representations to improve robustness, often employing model architectures such as deep Q-networks, actor-critic methods, and transformers. These advancements are significant because they address the critical challenge of generalization and reliability in RL, paving the way for safer and more dependable autonomous systems across various applications.

Papers

September 21, 2022

First-order Policy Optimization for Robust Markov Decision Process
Yan Li, Guanghui Lan, Tuo Zhao
Robust Policy Policy Mirror Descent First Order Policy Robust Markov Decision

September 20, 2022

Soft Action Priors: Towards Robust Policy Transfer
Matheus Centa, Philippe Preux
Reinforcement Learning Robust Policy Policy Distillation Action Prior

September 14, 2022

September 12, 2022

Deterministic Sequencing of Exploration and Exploitation for Reinforcement Learning
Piyush Gupta, Vaibhav Srivastava
Reinforcement Learning Markov Decision Process Optimal Policy Environment Exploration Robust Policy Deterministic Algorithm Cumulative Regret Real World eXploitation

August 11, 2022

Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity
Laixi Shi, Yuejie Chi
Offline Reinforcement Learning Robust Policy Value Iteration Distributionally Robust Model Based Offline Reinforcement Learning Tabular Markov Decision Process Robust Offline Reinforcement Learning

August 4, 2022

AG2U -- Autonomous Grading Under Uncertainties
Yakov Miron, Yuval Goldfracht, Chana Ross, Dotan Di Castro, Itzik Klein
Robust Policy Observable Markov Decision Process High Uncertainty Value Automatic Grading Localization Uncertainty Surface Roughness

August 3, 2022

Bayesian regularization of empirical MDPs
Samarth Gupta, Daniel N. Hill, Lexing Ying, Inderjit Dhillon
Markov Decision Process Optimal Policy Model Based Reinforcement Learning Robust Policy Entropy Regularization Bayesian Regularization MDP Model

July 19, 2022

Feasible Adversarial Robust Reinforcement Learning for Underspecified Environments
JB Lanier, Stephen McAleer, Pierre Baldi, Roy Fox
Robust Policy Robust Reinforcement Learning Adversarial Reinforcement Learning Adversarial Parameter

July 5, 2022

Robust Reinforcement Learning in Continuous Control Tasks with Uncertainty Set Regularization
Yuan Zhang, Jianhong Wang, Joschka Boedecker
Reinforcement Learning Regularization Model Robust Policy Robust Reinforcement Learning Continuous Control Task Real World Reinforcement Learning

May 31, 2022

Robust Anytime Learning of Markov Decision Processes
Marnix Suilen, Thiago D. Simão, David Parker, Nils Jansen
Markov Decision Process Sequential Decision Robust Policy Robust Continual Learning

May 27, 2022

Provably Sample-Efficient RL with Side Information about Latent Dynamics
Yao Liu, Dipendra Misra, Miro Dudík, Robert E. Schapire
Reinforcement Learning Reinforcement Learning Algorithm Robust Policy Latent State Sample Efficient Latent Dynamic Side Information Transfer Reinforcement Learning

May 15, 2022

Policy Gradient Method For Robust Reinforcement Learning
Yue Wang, Shaofeng Zou
Policy Gradient Robust Policy Robust Reinforcement Learning

May 9, 2022

Disturbance-Injected Robust Imitation Learning with Task Achievement
Hirotaka Tahara, Hikaru Sasaki, Hanbit Oh, Brendan Michael, Takamitsu Matsubara
Robust Policy Task Completion Robust Imitation Optimal Demonstration Disturbance Injection

March 16, 2022

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 13, 2022

Policy Learning for Robust Markov Decision Process with a Mismatched Generative Model
Jialian Li, Tongzheng Ren, Dong Yan, Hang Su, Jun Zhu
Policy Learning Robust Policy Partially Observable Markov Decision Process Optimal Robust Policy

February 14, 2022

Robust Policy Learning over Multiple Uncertainty Sets
Annie Xie, Shagun Sodhani, Chelsea Finn, Joelle Pineau, Amy Zhang
Reinforcement Learning Native Robustness Robust Policy Robust Reinforcement Learning Uncertainty Set Robust Controllable Set

February 11, 2022

Uncertainty Aware System Identification with Universal Policies
Buddhika Laknath Semage, Thommen George Karimpanal, Santu Rana, Svetha Venkatesh
Reinforcement Learning Robust Policy Domain Randomization Uncertain System Trained Policy Robust Bayesian Optimization

January 11, 2022

Learning Robust Policies for Generalized Debris Capture with an Automated Tether-Net System
Chen Zeng, Grant Hecht, Prajit KrisshnaKumar, Raj K. Shah, Souma Chowdhury, Eleonora M. Botta
Reinforcement Learning Proximal Policy Optimization Robust Policy Physical Actuation Tethered Robot Chaser Satellite

December 21, 2021

Off Environment Evaluation Using Convex Risk Minimization
Pulkit Katdare, Shuijing Liu, Katherine Driggs-Campbell
Reinforcement Learning Non Humanoid Robot Robot Person Empirical Risk Minimization Robust Policy