RL Control

RL: Reinforcement Learning

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Overview

Reinforcement learning control studies how agents can learn actions that steer dynamic systems toward goals while managing costs, constraints, and uncertainty. Common approaches include actor-critic methods such as PPO, SAC, and TD3; model-based learning with predictive control; and offline learning from logged data, often combined with safety filters or physical models. Work spans simulated benchmarks and applications such as robotics, traffic, buildings, power grids, and fluid flow, with evaluation increasingly testing hardware transfer and changing conditions. A central tension is that high simulated reward or average performance does not ensure safe, reliable behavior under real-world disturbances, limited data, or distribution shift.

Latest papers

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276 papers34 papers in the last four weeks, up 13% on the four weeks before. 0.2% of all new papers.

  1. Soft Deterministic Policy Gradient with Gaussian Smoothing

    May 7, 2026Hyunjun Na, Donghwan LeeRL ControlPolicy Gradient

    School of Electrical Engineering, KAIST 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea

  2. Offline Reinforcement Learning for Rotation Profile Control in Tokamaks

    May 7, 2026Rohit Sonker, Hiro Josep Farre Kaga, Jiayu Chen +5RL ControlOffline RL

    1Robotics Institute, Carnegie Mellon University · 2Princeton University · 4The University of Hong Kong +2

  3. Hidden States as Value Gradients: The Pontryagin Structure of Recurrent Policies

    May 6, 2026David Leeftink, Max Hinne, Marcel van GervenRL ControlReinforcement Learning

    Department of Machine Learning and Neural Computating Donders Institute for Brain, Cognition and Behaviour Radboud University, Nijmegen, the Netherlands.

  4. Worst-Case Discovery and Runtime Protection for RL-Based Network Controllers

    May 6, 2026Hongyu Hè, Minhao Jin, Maria ApostolakiRL ControlSafe RL

    Princeton

  5. Sim-to-Real Transfer and Robustness Evaluation of Reinforcement Learning Control with Integrated Perception on an ASV for Floating Waste Capture

    May 4, 2026Luis F. W. Batista, Stéphanie Aravecchia, Cédric PradalierRL ControlSim-to-Real Transfer

    GeorgiaTech Europe - IRL2958 GT-CNRS, Metz, France

  6. Closed-Loop CO2 Storage Control With History-Based Reinforcement Learning and Latent Model-Based Adaptation

    May 4, 2026Sofianos Panagiotis Fotias, Vassilis GaganisRL ControlLatent Dynamics Modeling

    School of Mining and Metallurgical Engineering, National Technical University of Athens, Athens 157 73, Greece · Institute of Geoenergy, Foundation for Research and Technology, Chania, 73100, Greece

  7. Reinforcement Learning Trained Observer Control for Bearings-Only Tracking

    May 4, 2026Branko Ristic, Sanjeev ArulampalamRL Control

    School of Engineering, RMIT University, Melbourne, VIC3000, Australia · Defence Science and Technology Group, Australia

  8. Stability of Control Lyapunov Function Guided Reinforcement Learning

    May 3, 2026Zachary Olkin, William D. Compton, Aaron D. AmesRL ControlLyapunov Stability

    The authors are with the Department of Control and Dynamical Systems at the California Institute of Technology.

  9. Remote Action Generation: Remote Control with Minimal Communication

    May 3, 2026Szymon Kobus, Deniz GündüzRL ControlReinforcement Learning

    Electrical and Electronic Engineering Imperial College London

  10. Zero-Shot, Safe and Time-Efficient UAV Navigation via Potential-Based Reward Shaping, Control Lyapunov and Barrier Functions

    May 3, 2026Ashik Abrar Naeem, Mohammad Ariful HaqueRL ControlControl Lyapunov Functions

  11. Bi-Level Reinforcement Learning Control for an Underactuated Blimp via Center-of-Mass Reconfiguration

    May 2, 2026Xiaorui Wang, Hongwu Wang, Yue Fan +2RL ControlAerial Robotics

  12. An Automatic Ground Collision Avoidance System with Reinforcement Learning

    Apr 27, 2026Seyyid Osman Sevgili, Atahan Cilan, Mahir Demir +2RL ControlCollision Avoidance

    Turkish Aerospace Istanbul, Turkey

  13. An Aircraft Upset Recovery System with Reinforcement Learning

    Apr 27, 2026Mahir Demir, Atahan Cilan, Seyyid Osman Sevgili +2RL Control

    Turkish Aerospace Istanbul, Turkey

  14. Perfecting Aircraft Maneuvers with Reinforcement Learning

    Apr 27, 2026Atahan Cilan, Mahir Demir, Özgün Can Yürütken +2RL Control

    Turkish Aerospace Istanbul, Turkey

  15. MUSIC: Learning Muscle-Driven Dexterous Hand Control

    Apr 26, 2026Pei Xu, Yufei Ye, Shuchun Sun +3Robotic ControlRL Control

    Stanford University, USA · Clemson University, USA

  16. GIFT: Global stabilisation via Intrinsic Fine Tuning

    Apr 25, 2026Rory Young, Nicolas PugeaultRL ControlReinforcement Learning

    School of Computing Science University of Glasgow

  17. Insect-inspired modular architectures as inductive biases for reinforcement learning

    Apr 23, 2026Anne E. StaplesRL ControlReinforcement Learning

    Department of Mechanical Engineering, Virginia Tech, Blacksburg, Virginia 24061, USA

  18. A Systematic Review and Taxonomy of Reinforcement Learning-Model Predictive Control Integration for Linear Systems

    Apr 22, 2026Mohsen Jalaeian Farimani, Roya Khalili Amirabadi, Davoud Nikkhouy +3RL ControlModel Predictive Control

    Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Milan, Italy · Department of Applied Mathematics, Ferdowsi University of Mashhad, Mashhad, Iran · Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran +2

  19. Safe Continual Reinforcement Learning in Non-stationary Environments

    Apr 21, 2026Austin Coursey, Abel Diaz-Gonzalez, Marcos Quinones-Grueiro +1RL ControlNon-Stationary RL

    Institute for Software Integrated Systems, Vanderbilt University

  20. RL-ABC: Reinforcement Learning for Accelerator Beamline Control

    Apr 21, 2026Anwar Ibrahim, Fedor Ratnikov, Maxim Kaledin +2RL ControlHigh-Energy Physics

  21. Safe Deep Reinforcement Learning for Building Heating Control and Demand-side Flexibility

    Apr 17, 2026Colin Jüni, Mina Montazeri, Yi Guo +3RL ControlBuilding Energy Management

    Urban Energy Systems Laboratory, Swiss Federal Laboratories for Materials Science and Technology, Dubendorf, Switzerland. · School of Automation, Beijing Institute of Technology, Haidian District, Beijing, China · Reliability and Risk Engineering Laboratory, ETH Zürich, CH-8092, Switzerland.

  22. Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions

    Apr 15, 2026Kristian Holme, Jean Rabault, Ricardo Vinuesa +1RL Control

    University of Oslo · Independent Researcher, Oslo · University of Michigan

  23. Contextual Multi-Task Reinforcement Learning for Autonomous Reef Monitoring

    Apr 14, 2026Melvin Laux, Yi-Ling Liu, Rina Alo +4RL ControlUnderwater Robotics

    Robotics Research Group, University of Bremen, Bremen, Germany · Robotics Innovation Center, German Research Center for Artificial Intelligence, Bremen, Germany

  24. A Comparison of Reinforcement Learning and Optimal Control Methods for Path Planning

    Apr 14, 2026Qiang Le, Yaguang Yang, Isaac E. WeintraubSafe Motion PlanningAutonomous Driving Planning

    Department of Electrical and Computer Engineering, Hampton University Hampton, USA · Air Warfare Directorate, Air Force Research Laboratory Wright-Patterson, USA

  25. Hierarchical RL-MPC Control for Dynamic Wake Steering in Wind Farms

    Apr 13, 2026Marcus Binder Nilsen, Teodor Olof Benedict Åstrand, Tuhfe Göçmen +1RL ControlModel Predictive Control

    Technical University of Denmark, Department of Wind and Energy Systems. Roskilde, Frederiksborgvej 399, Denmark

  26. Accelerating Reinforcement Learning for Wind Farm Control via Expert Demonstrations

    Apr 13, 2026Marcus Binder Nilsen, Julian Quick, Tuhfe Göçmen +2RL ControlOffline-To-Online RL

    Department of Wind and Energy Systems, Technical University of Denmark, Roskilde, Denmark

  27. ScoRe-Flow: Complete Distributional Control via Score-Based Reinforcement Learning for Flow Matching

    Apr 13, 2026Xiaotian Qiu, Lukai Chen, Jinhao Li +3RL for Flow Matching ModelsFlow-Based Policy Learning

    Zhejiang University, Hangzhou, China · Shanghai Innovation Institute · Shanghai Jiao Tong University, Shanghai, China +1

  28. Physics-Informed Reinforcement Learning of Spatial Density Velocity Potentials for Map-Free Racing

    Apr 10, 2026Shathushan Sivashangaran, Apoorva Khairnar, Sepideh Gohari +2Autonomous RacingRL Control

    Autonomous Robots and Vehicles Laboratory, College of Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA. · Department of Mechanical Engineering, Virginia Tech, Blacksburg, VA 24061, USA. · Robotics Department, University of Michigan, Ann Arbor, MI 48109, USA.

  29. Physics-guided surrogate learning enables zero-shot control of turbulent wings

    Apr 10, 2026Yuning Wang, Pol Suarez, Mathis Bode +1RL ControlComputational Fluid Dynamics

    Department of Aerospace Engineering, University of Michigan, Ann Arbor, MI 48109, USA. · FLOW, Engineering Mechanics, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden. · Jülich Supercomputing Centre, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany

  30. Musculoskeletal Motion Imitation for Learning Personalized Exoskeleton Control Policy in Impaired Gait

    Apr 10, 2026Itak Choi, Ilseung Park, Eni Halilaj +1Hip Exoskeleton ControlAssistive Robotics

    Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213 USA.