Policy Learning

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Overview

Policy learning studies how to choose actions or interventions over time to improve rewards, welfare, or other goals, often when outcomes are uncertain or feedback is limited. Common approaches include policy-gradient and actor–critic reinforcement learning, value-based and offline learning, imitation from demonstrations, and direct learning of treatment or resource-allocation rules. Current work also tackles long-horizon language-model agents and generative robot policies, using methods such as finer-grained credit assignment, exploration, memory, and policy reuse. A central tension is achieving reliable, safe learning with theoretical guarantees while using expressive policies and imperfect data or rewards efficiently.

Latest papers

CardsList

488 papers74 papers in the last four weeks, up 48% on the four weeks before. 0.4% of all new papers.

  1. ARLArena: A Unified Framework for Stable Agentic Reinforcement Learning

    Feb 25, 2026Xiaoxuan Wang, Han Zhang, Haixin Wang +11Agentic RLReinforcement Learning

    Department of Computer Science, University of California, Los Angeles, California, USA · University of Wisconsin–Madison, Madison, Wisconsin, USA

  2. On the Structural Non-Preservation of Epistemic Behaviour under Policy Transformation

    Feb 24, 2026Alexander GalozyReinforcement LearningPartially Observable RL

    Center for Applied Intelligent Systems Research, Halmstad University, Sweden

  3. A Generalized Apprenticeship Learning Framework for Capturing Evolving Student Pedagogical Strategies

    Feb 24, 2026Md Mirajul Islam, Xi Yang, Adittya Soukarjya Saha +2AI in EducationPolicy Learning

    North Carolina State University, Raleigh, NC 27606, USA · IBM Research, Yorktown Heights, NY 10598, USA

  4. Gradient Regularization Mitigates Reward Hacking in Reinforcement Learning from Human Feedback and Verifiable Rewards

    Feb 20, 2026Johannes Ackermann, Michael Noukhovitch, Takashi Ishida +1Reward HackingReinforcement Learning with Verifiable Rewards

    The University of Tokyo · Mila · RIKEN AIP

  5. POP: Prior-Fitted First-Order Optimization Policies

    Feb 17, 2026Jan Kobiolka, Christian Frey, Gresa Shala +3Learning to OptimizeAdaptive Gradient Methods

    Department of Computer Science University of Technology Nuremberg Germany · Department of Computer Science Albert Ludwig University of Freiburg Germany · Faculty of Natural Sciences University of Elbasan Albania

  6. TSR: Trajectory-Search Rollouts for Multi-Turn RL of LLM Agents

    Feb 12, 2026Aladin Djuhera, Swanand Kadhe, Farhan Ahmed +3Tree SearchLLM Agent Training

    Technical University Munich · IBM Research

  7. On the Role of Computation in Reinforcement Learning

    Feb 5, 2026Raj Ghugare, Michał Bortkiewicz, Alicja Ziarko +1Reinforcement LearningModel-Free RL

    Department of Computer Science, Princeton University · Warsaw University of Technology · University of Warsaw +2

  8. Constrained Group Relative Policy Optimization

    Feb 5, 2026Roger Girgis, Rodrigue de Schaetzen, Luke Rowe +3Group Relative Policy OptimizationConstrained RL

    Mila – Quebec AI Institute Université de Montréal

  9. QUATRO: Query-Adaptive Trust Region Policy Optimization for LLM Fine-tuning

    Feb 4, 2026Doyeon Lee, Eunyi Lyou, Hyunsoo Cho +3Trust-Region OptimizationPolicy Learning

    Seoul National University · Department of Artificial Intelligence / Institute for Multiscale Matter and Systems, Ewha Woman University · Geogia Institute of Technology

  10. Just-In-Time Reinforcement Learning: Continual Learning in LLM Agents Without Gradient Updates

    Jan 26, 2026Yibo Li, Zijie Lin, Ailin Deng +5Continual Learning for LLM AgentsReinforcement Learning

    National University of Singapore, Singapore.

  11. R2^2PO: Decoupling Rollout and Inference Policies for LLM Reasoning

    Jan 17, 2026Jingchu Wang, Bingbing Xu, Yige Yuan +4RL for Language Model ReasoningPolicy Optimization

    State Key Laboratory of AI Safety, Institute of Computing Technology, CAS · University of Chinese Academy of Sciences · National University of Singapore

  12. DeFlow: Decoupling Behavior-Prior Modeling and Value Maximization for Offline Policy Extraction

    Jan 15, 2026Zhancun Mu, Chi ZhangOffline RLPolicy Learning

    Peking University, Institute of Artificial Intelligence, China, Beijing.

  13. Soft Fitted Q-Iteration without Bellman Completeness: Occupancy Reweighting and Temperature Annealing

    Dec 30, 2025Lars van der Laan, Nathan KallusReinforcement LearningKL-Regularized RL

    Department of Statistics, University of Washington · Netflix · Cornell University

  14. SB-TRPO: Towards Safe Reinforcement Learning with Hard Constraints

    Dec 29, 2025Dominik Wagner, Ankit Kanwar, Luke OngSafety-Critical ControlPolicy Optimization

    NTU Singapore · Sony Corporation

  15. Trust Region Masking for Long-Horizon LLM Reinforcement Learning

    Dec 28, 2025Yingru Li, Jiacai Liu, Jiawei Xu +4RL for Language ModelsReinforcement Learning

    Fudan University · The Chinese University of Hong Kong, Shenzhen

  16. Auto-exploration for online reinforcement learning

    Dec 6, 2025Caleb Ju, Guanghui LanPolicy OptimizationRL Exploration

  17. Diffusion-Augmented Markov Decision Processes for Maximum Entropy Reinforcement Learning

    Dec 1, 2025Sebastian Sanokowski, Kaustubh Patil, Majid KhadivRL ControlDiffusion Policy

    Munich Institute of Robotics and Machine Intelligence (MIRMI), Technical University Munich · Practical Project Student Exchange Program, Technical University Munich · MIT World Peace University

  18. Iterative Policy Optimization: Batch-Online Multi-Turn RL via Single-Turn RL

    Nov 26, 2025Daniel R. Jiang, Ankur Samanta, Yukai Yang +3Reinforcement LearningPolicy Iteration

    Meta · Columbia University · FAIR at Meta

  19. Learning to Reason Efficiently with Discounted Reinforcement Learning

    Oct 27, 2025Alex Ayoub, Kavosh Asadi, Dale Schuurmans +2Reinforcement LearningRL for Language Model Reasoning

    Amazon, University of Alberta · Amazon · University of Alberta

  20. Why Do LLM Agents Fail in Exploring New Environments? A World-Modeling Perspective

    Oct 16, 2025Shiqi Chen, Tongyao Zhu, Zian Wang +8RL ExplorationPolicy Learning

    City University of Hong Kong · National University of Singapore · The Hong Kong Polytechnic University +5

  21. Frictional Q-Learning

    Sep 24, 2025Hyunwoo Kim, Hyo Kyung LeeReinforcement LearningQ-Learning

    Data Analysis and Healthcare System Lab, Korea University, Seoul, Korea.

  22. Reinforcement Learning in MDPs with Information-Ordered Policies

    Aug 5, 2025Zhongjun Zhang, Shipra Agrawal, Ilan Lobel +2Queueing TheoryPolicy Learning

    Department of Industrial Engineering and Management Sciences, Northwestern University · Department of Industrial Engineering and Operations Research, Columbia University · Technology, Operations, and Statistics, Stern School of Business, New York University +1

  23. 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

  24. Fully Offline Reinforcement Learning

    May 28, 2025Mattie Fellows, Clarisse Wibault, Uljad Berdica +3Bayesian RLOffline RL

    Foerster Lab for AI Research (FLAIR), Department of Engineering Science, University of Oxford · Machine Learning Research Group, Department of Engineering Science, University of Oxford

  25. Distributionally Robust Deep Q-Learning

    May 25, 2025Chung I Lu, Julian Sester, Aijia ZhangRobust Markov Decision ProcessesDeep Q-Learning

    National University of Singapore, Department of Mathematics, 21 Lower Kent Ridge Road, 119077.

  26. Meta-reinforcement learning with minimum attention

    May 22, 2025Shashank Gupta, Pilhwa LeeMeta-Reinforcement LearningPolicy Learning

    Department of EECS University of Michigan Ann Arbor, MI 48109 · Department of Mathematics Morgan State University Baltimore, MD 21251

  27. Adaptive Resolving Methods for Markov Decision Processes with Function Approximations

    May 17, 2025Jiashuo Jiang, Yinyu Ye, Yiming ZongMarkov Decision ProcessesReinforcement Learning

    Department of Industrial Engineering & Decision Analytics, The Hong Kong University of Science and Technology · Department of Management Science & Engineering, Stanford University

  28. Reinforcement Learning for Individual Optimal Policy from Heterogeneous Data

    May 14, 2025Rui Miao, Babak Shahbaba, Annie QuOffline RLPolicy Learning

    National Heart, Lung, and Blood Institute · University of California, Irvine

  29. Rethinking the Global Convergence of Softmax Policy Gradient with Linear Function Approximation: The Case of Multi-Armed Bandits

    May 6, 2025Max Qiushi Lin, Jincheng Mei, Matin Aghaei +6Multi-Armed BanditsPolicy Gradient

    Simon Fraser University · Google DeepMind · Google Research +1

  30. ACT-JEPA: Novel Joint-Embedding Predictive Architecture for Efficient Policy Representation Learning

    Jan 24, 2025Aleksandar Vujinovic, Aleksandar KovacevicRepresentation LearningWorld Model Learning

    Faculty of Technical Sciences, University of Novi Sad