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. Dream-COP: Guiding Algorithm Discovery for Combinatorial Optimization Problems in an Experience World

    Oct 27, 2026Kuan Xu, Jianming Wang, Ni Zhang +3Automated Algorithm DiscoveryCombinatorial Optimization

    Singapore Management University · University of Science and Technology of China · Eindhoven University of Technology +1

  2. A generalist policy for muscle-driven control across individual musculoskeletal models

    Oct 27, 2026Bozhao Wang, Yinglei Zhu, Zhengqing Li +7Policy LearningMusculoskeletal Modeling

    State Key Laboratory of Tribology in Advanced Equipment, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China · Beijing Key Laboratory of Transformative High-end Manufacturing Equipment and Technology, Tsinghua University, Beijing 100084, China

  3. PolicyMediator: Multi-Regional Policy Learning through Mediation Agents with Evolving Skills in OPC Ecosystems

    Oct 26, 2026Jie Li, Bin Guo, Georgina Curto +3Policy LearningPolicy Optimization

    Northwestern Polytechnical University, Xi’an, China · United Nations University Institute in Macau, Macau, China

  4. MimicAll: Structured Embodiment Conditioning for Cross-Humanoid Whole-Body Motion Tracking

    Oct 24, 2026Jia Li, Lingyun Xu, Yitang Li +1Humanoid Motion TrackingCross-Embodiment Robot Learning

    Huazhong University of Science and Technology · Peking University · Tsinghua University +1

  5. Doubly Robust Distributionally Robust Offline Contextual Pricing

    Oct 22, 2026Min Xu, Xinyi Yin, Yunfan Zhang +3Off-Policy EvaluationDistributionally Robust Optimization

    School of Management and Engineering, Nanjing University, Nanjing, China · School of Mathematics, Nanjing University, Nanjing, China · Stern School of Business, New York University, New York, USA

  6. Solvable models of learning to pursue a moving target

    Oct 22, 2026John J. Vastola, Kanaka RajanLinear Quadratic RegulatorPolicy Learning

    Department of Neurobiology, Harvard Medical School · Department of Psychology and Center for Brain Science, Harvard University · Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University

  7. TerraTransfer++: Demonstration-Free End-to-End Planner

    Oct 21, 2026Zikang Xiong, Weixin Li, Zhouchonghao Wu +6End-to-End Autonomous DrivingAutonomous Driving Planning

    Applied Intuition · University of California, Los Angeles · University of California, Berkeley

  8. When Does Feedback Help? Auditing Learned Voltage-Clamp Experimental Design

    Oct 20, 2026Rayan Nyaupane, Abhiram BhupatirajuActive Experimental DesignFeedback Control

    The University of Texas at Austin

  9. Deep Pontryagin Learning for Continuous-Time Stochastic Control with Jumps

    Oct 19, 2026Jean-Loup Dupret, Patrick CheriditoStochastic Optimal ControlPolicy Learning

    Department of Mathematics and RiskLab, ETH Zurich, Rämistrasse 101, Zurich, 8092, Switzerland

  10. Conditional Average Treatment Effect Distillation for Hypothetical State-Intervention Targeting Under Budget Constraints

    Oct 19, 2026Vasundhara Acharya, Bülent YenerPolicy LearningCausal Effect Estimation

    Rensselaer Polytechnic Institute, Troy, USA

  11. Distributionally-Robust Policy Learning with Observational Data

    Oct 18, 2026Debmalya MandalPolicy LearningDistribution Shift Robustness

    Dept. of Computer Science University of Warwick, UK

  12. Paired-Outcome Learning for Selective Spacecraft Attitude Capture under Torque Limits

    Oct 17, 2026Donghe Chen, Jia Deng, Zehao Jia +2Policy LearningAdaptive Control

    School of Astronautics, Beihang University, Beijing 100191, China · Astroup(Beijing) Technology Co., Ltd.

  13. OpCredit: Operation-Aware Policy Learning for Agentic Knowledge Graph Question Answering

    Oct 15, 2026Yucheng Li, Mingyuan Li, Xiaxia Wang +1Knowledge Graph Question AnsweringPolicy Learning

    State Key Laboratory of Novel Software Technology, Nanjing University, Nanjing, China · Department of Computer Science, University of Oxford

  14. Value-Guided Repulsion for Offline Reinforcement Learning

    Oct 14, 2026Yixue Hao, Jiahao Zhang, Jiesong Lian +5Offline RLPolicy Learning

    School of Computer Science and Technology, Huazhong University of Science and Technology

  15. Occupancy Modeling via Drifting: One-Step Generation Enables Direct Policy Extraction

    Oct 14, 2026Robin Uhrich, Marco Bagatella, Núria Armengol Urpí +2Reinforcement LearningPolicy Learning

    University of Tübingen · ETH Zürich · Max Planck Institute for Intelligent Systems

  16. RoboSpan: Learning Modular Coordination Policies for High-DoF Whole-Body Mobile Manipulation with Teleoperation

    Oct 14, 2026Keqiang Ren, Xuecheng Ye, Hanyu Liu +6Whole-Body Robotic ManipulationLong-Horizon Robotic Manipulation

    Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology, School of Mechanical Engineering, Jiangnan University, Wuxi 214122, China.

  17. Learning Deployable Causal Action Geometry under Temporal Non-Stationarity

    Oct 12, 2026Changjian Liu, Tianyu Wang, Yuwei Xu +6Dose-Response EstimationCausal Effect Estimation

    Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing, China · Beijing Key Laboratory of Spatio-temporal Perception and Urban Resilience · Taobao & Tmall Group of Alibaba, Beijing, China +2

  18. Notes on Uniform Policy Score Bounds and Lipschitz Continuity for Truncated Gaussian, Product Cauchy, Boltzmann, and Softmax Policies

    Oct 11, 2026Yanjie DongPolicy Learning

    Xi’an Jiaotong University

  19. Physics Foundation Models for Efficient Control of Fluid Flows

    Oct 10, 2026Mahindra Rautela, Shaifalee Saxena, Alexander ScheinkerPhysical Foundation ModelsPolicy Learning

    Los Alamos National Laboratory, Los Alamos, NM, USA · University of New Mexico, Albuquerque, NM, USA

  20. Higher-Order Action Supervision Makes A Strong Policy Class

    Oct 8, 2026Peng Cheng, Yunxian Hou, Zhi Zhou +3Policy LearningRobust RL

    Institute for AI Industry Research (AIR), Tsinghua University · Zenfex AI Lab · University of Electronic Science and Technology of China +1

  21. Learning How to Search for Plans with Exponentially Less Space

    Oct 7, 2026Dominik Drexler, Simon Ståhlberg, Markus Fritzsche +1Symbolic PlanningPolicy Learning

    Linköping University Linköping, Sweden · RWTH Aachen University Aachen, Germany · Universidad Simón Bolívar Caracas, Venezuela

  22. Policy Learning with Weak Signals

    Oct 7, 2026Benedikt Koch, Winston Chou, Aurélien Bibaut +1Policy LearningCausal Effect Estimation

    Harvard University · Netflix

  23. Learning Situation-Conditioned Thinking Policies for Long-Term LLM Agents

    Oct 7, 2026Hong SuLLM Agent MemoryLong-Horizon LLM Agents

    School of Computer Science, Chengdu University of Information Technology, Chengdu, China

  24. Towards the Automatic Synthesis of Interpretable Chess Tactics

    Oct 6, 2026Abhijeet Krishnan, Chris MartensGame-Playing AgentsChess

    North Carolina State University Venture IV, 1730 Varsity Dr, Raleigh, NC 27606

  25. Learning Explainable Representations of Complex Game-playing Strategies

    Oct 6, 2026Abhijeet Krishnan, Colin M. Potts, Arnav Jhala +3Game-Playing AgentsProgram Synthesis

    Venture IV 420, North Carolina State University, Raleigh, NC 27606 USA · Department of Aerospace Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, Maharashtra, India · Tata Research Development and Design Centre, Pune 411013, Maharashtra, India +1

  26. ForkPilot: Self-Evolving Policy for Retrospective Search in Long-Horizon Agents

    Oct 4, 2026Xinyue Zeng, Shivam Shandilya, Guilherme Potje +6LLM AgentsLong-Horizon LLM Agents

    Virginia Tech · Microsoft

  27. Learning Modular Policy for Multi-Floor Object Navigation:A Factorized Framework for Diagnostic Study

    Oct 3, 2026Shichao Zhai, Shuhao Ye, Rong Xiong +1Object-Goal NavigationEmbodied Navigation

    State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, China.

  28. Single or Multiple Policies for Phase-Structured Reinforcement Learning?

    Oct 2, 2026Guilhem Loussouarn, Nancy Nayak, Kin K. LeungReinforcement LearningNon-Stationary RL

    Department of Electrical and Electronic Engineering Imperial College London, UK

  29. Targeted Active Learning for Preference-Based Treatment Effects on Multivariate Outcomes

    Oct 2, 2026Lola Giordani, Mathieu Even, Chloé Geoffroy +3Active Preference LearningIndividualized Treatment Effect Estimation

    Theremia, Paris · Paris Brain Institute (ICM), Sorbonne Université, Inserm, CNRS, AP-HP · Inria, Inserm, Université de Montpellier, France +1

  30. Multi-Fidelity Policy Gradients Stabilize Data-Scarce Reinforcement Learning

    Oct 1, 2026Xinjie Liu, Ruihan Zhao, Anirban Chaudhuri +3Policy Gradient MethodsPolicy Learning

    University of Texas at Austin · University of British Columbia