Distributionally Robust RL

RL: Reinforcement Learning

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Overview

Distributionally robust reinforcement learning seeks policies that retain good performance when the true dynamics, rewards, or deployment tasks differ from those seen during training. Common approaches define ambiguity sets using Wasserstein distance, total variation, or divergence measures, then optimize worst-case Bellman values with robust Q-learning, actor-critic, or planning methods. Work spans tabular and function-approximation settings, average-reward control, safety, offline learning, multi-agent games, and reinforcement learning from human feedback. A central tension is that larger uncertainty sets can improve protection against distribution shift but cause excessive pessimism and higher sample costs; support mismatch can make reliable learning impossible without additional assumptions or useful side information.

Latest papers

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34 papers0 papers in the last four weeks, down 100% on the four weeks before. 0.0% of all new papers.

  1. Provably Efficient Q-learning for Robust Reinforcement Learning

    Oct 26, 2026Yuchen Jiao, Gen LiRobust RLDistributionally Robust RL

    Department of Statistics and Data Science, Chinese University of Hong Kong.

  2. RSD-Poker: Structure-Adaptive and Shift-Robust Risk-Utility Certification for Residual Policies in Imperfect-Information Games

    Sep 27, 2026Miaobo Hu, Shuhao Hu, Xiaobo Guo +4Distribution Shift RobustnessImperfect-Information Games

    School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China · Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China

  3. Distributionally Robust Average-Reward Reinforcement Learning: Finite-Sample Guarantees under Weak Communication

    Sep 26, 2026Chenyu Lu, Zijun Chen, Nian SiDistributionally Robust RLAverage-Reward RL

    The Hong Kong University of Science and Technology

  4. Interactive Distributionally Robust Multi-Agent Learning with General Function Approximation

    Sep 25, 2026Debamita Ghosh, George K. Atia, Yue WangFunction Approximation in RLReinforcement Learning

    Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL 32816, USA · Department of Computer Science, University of Central Florida, Orlando, FL 32816, USA

  5. Statistical Convergence of Transformer Encoder-Accelerated Robust Reinforcement Learning

    Sep 20, 2026Suman Banerjee, Hiroyasu TsukamotoReinforcement LearningTransformer-Based RL

    Department of Aerospace Engineering, The Grainger College of Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA

  6. Online Robust Reinforcement Learning Through Monte-Carlo Planning

    Sep 16, 2026Tuan Dam, Kishan Panaganti, Brahim Driss +1Monte Carlo Tree SearchDistributionally Robust RL

    Hanoi University of Science and Technology, Hanoi, Vietnam · Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA, USA · Univ. Lille, Inria, CNRS, Centrale Lille, UMR 9189-CRIStAL

  7. Quantifying Risk Under Evolving Uncertainty: Belief-Dependent Robustness for Safe Sequential Decision Making

    Aug 18, 2026Deep Kumar Ganguly, Jan KretinskyRisk-Sensitive PlanningRobust RL

    Technical University of Munich, Germany · Masaryk University, Brno, Czech Republic

  8. Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions

    Aug 6, 2026Yuepeng Yang, Yuxin Chen, Yuejie ChiRobust Markov Decision ProcessesAverage-Reward RL

    *Department of Statistics and Data Science, Yale University. · †Department of Statistics and Data Science, the Wharton School, University of Pennsylvania.

  9. Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning

    Jul 3, 2026Jialun Cao, Fernando Acero, David Šiška +1Robust Markov Decision ProcessesMaximum Entropy RL

    School of Mathematics, University of Edinburgh, United Kingdom. · J.P. Morgan AI Research, United Kingdom. · Department of Mathematics, Imperial College London, United Kingdom.

  10. Stationary Robust Mean-Field Games under Model Mismatches

    Jun 21, 2026Yue WangMean Field GamesGame Theory

    Department of Electrical and Computer Engineering University of Central Florida Orlando, Florida, USA

  11. Robust QQ-learning for mean-field control under Wasserstein uncertainty in common noise

    Jun 18, 2026Mathieu Laurière, Ariel Neufeld, Kyunghyun ParkQ-LearningWasserstein Distributionally Robust Optimization

    NYU Shanghai HPC · MOE AcRF Tier 1 Grant RG109/25 · National Research Foundation of Korea

  12. A Unifying Lens on Reward Uncertainty in RLHF

    Jun 8, 2026Ely Hahami, Yoel Zimmermann, Ray Zhou +1Reward ModelingKL-Regularized RL

    Harvard College, Harvard University, Cambridge, MA, USA · John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA

  13. Distributionally Robust Multi-Task Reinforcement Learning via Adaptive Task Sampling

    May 14, 2026Nicholas E. Corrado, Wenyuan Huang, Josiah P. HannaDistributionally Robust RLMulti-Task RL

    Computer Sciences Department · University of Wisconsin – Madison

  14. Central Limit Theorem for Two-Time-Scale Approximate Distributionally Robust RL

    May 8, 2026Shengbo Wang, Zexi ZhangStochastic ApproximationDistributionally Robust RL

    Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California

  15. Quantile Geometry Regularization for Distributional Reinforcement Learning

    May 5, 2026Zhaofan Zhang, Minghao Yang, Rufeng Chen +2Distributional RLQuantile Regression

    Information Hub, AI Thrust Hong Kong University of Science and Technology (Guangzhou) Guangzhou, Guangdong, China

  16. Taming the Curses of Multiagency in Robust Markov Games with Large State Space through Linear Function Approximation

    May 4, 2026Jingchu Gai, Laixi ShiMulti-Agent System OptimizationMarkov Models

    Machine Learning Department, Carnegie Mellon University. · Department of Electrical and Computer Engineering, Johns Hopkins University, MD 21286, USA.

  17. Wasserstein Distributionally Robust Regret Optimization for Reinforcement Learning from Human Feedback

    Apr 30, 2026Yikai Wang, Shang Liu, Jose BlanchetReward Over-OptimizationRegret Minimization in RL

    Department of Statistics and Operations Research, University of North Carolina · Imperial Business School, Imperial College London · Department of Management Science and Engineering, Stanford University

  18. A Distributionally Robust Reinforcement Learning Framework for Constrained Urban EV Dispatch

    Apr 28, 2026An Nguyen, Hoang Nguyen, Phuong Le +3Electric Vehicle ChargingConstrained RL

    College of Engineering and Computer Science, VinUniversity, Hanoi, Vietnam · Center for Environmental Intelligence, VinUniversity, Hanoi, Vietnam

  19. Robust Optimization for Mitigating Reward Hacking with Correlated Proxies

    Apr 13, 2026Zixuan Liu, Xiaolin Sun, Zizhan ZhengReward HackingRobust RL

    Department of Computer Science Tulane University New Orleans, LA 70118, USA

  20. Robust Adversarial Policy Optimization Under Dynamics Uncertainty

    Apr 13, 2026Mintae Kim, Koushil SreenathAdversarial MARLReinforcement Learning

    Hybrid Robotics, UC Berkeley Berkeley, CA 94720, USA

  21. Distributionally Robust Token Optimization in RLHF

    Mar 27, 2026Yeping Jin, Jiaming Hu, Ioannis Ch. PaschalidisLanguage Model RobustnessReasoning Consistency in Language Models

    Department of System Engineering Boston University, Boston, MA 02215, USA · Department of Math & Statistics Boston University, Boston, MA 02215, USA

  22. RE-SAC: Disentangling aleatoric and epistemic risks in bus fleet control: A stable and robust ensemble DRL approach

    Mar 19, 2026Yifan Zhang, Liang Zheng, Qifan ZhangUncertainty Estimation in RLReinforcement Learning

    Central South University

  23. Robust Regularized Policy Iteration under Transition Uncertainty

    Mar 10, 2026Hongqiang Lin, Zhenghui Fu, Weihao Tang +4Offline RLRobust RL

    College of Computer Science and Technology, Zhejiang University, Hangzhou, China · School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China · School of Software Technology, Zhejiang University, Hangzhou, China +2

  24. Robust Transfer Learning with Side Information

    Mar 9, 2026Akram S. Awad, Shihab Ahmed, Yue Wang +1Reinforcement LearningRobust Markov Decision Processes

    Department of Electrical and Computer Engineering, University of Central Florida, USA · Department of Computer Science, University of Central Florida, USA

  25. Adversarial Latent-State Training for Robust Policies in Partially Observable Domains

    Mar 7, 2026Angad Singh AhujaRobust RLPartially Observable RL

    Constrained Image-Synthesis Lab

  26. Learning-Based Robust Control: Unifying Exploration and Distributional Robustness for Reliable Robotics via Free Energy

    Mar 6, 2026Hozefa Jesawada, Giovanni Russo, Abdalla Swikir +1Robust ControlDistributionally Robust RL

    Mechanical Engineering Program, New York University Abu Dhabi, Abu Dhabi, UAE. · Department of Information and Electrical Engineering & Applied Mathematics, University of Salerno, Fisciano, Italy. · Mohammed bin Zayed University for Artificial Intelligence, Abu Dhabi, UAE.

  27. Fuz-RL: A Fuzzy-Guided Robust Framework for Safe Reinforcement Learning under Uncertainty

    Feb 24, 2026Xu Wan, Chao Yang, Cheng Yang +2Safe RLReinforcement Learning

    Zhejiang University · Alibaba DAMO Academy · Peking University

  28. Finite-Time Convergence of Single-Trajectory Chi-Square Robust Q-Learning With Linear Function Approximation

    Oct 2, 2025Saptarshi Mandal, Yashaswini Murthy, R. SrikantQ-LearningDistributionally Robust RL

    ECE, UIUC · ORIE, UT Austin · ECE, CSL, and the director of NCSA at UIUC

  29. Distributionally Robust Markov Games with Average Reward

    Aug 5, 2025Zachary Roch, Yue WangNash Equilibrium ComputationMulti-Agent System Optimization

    Department of Electrical and Computer Engineering, University of Central Florida, Orlando, Florida, USA. · Department of Computer Science, University of Central Florida, Orlando, Florida, USA.

  30. Efficient Q-Learning and Actor-Critic Methods for Robust Average-Reward Reinforcement Learning

    Jun 8, 2025Yang Xu, Swetha Ganesh, Vaneet AggarwalRobust Markov Decision ProcessesReinforcement Learning

    Purdue University, West Lafayette, Indiana, USA 47907