Model-Based RL

RL: Reinforcement Learning

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Overview

Model-based reinforcement learning studies how agents can learn or use a model of how actions change the environment, then plan with that model to improve decisions and reduce costly interaction. Common approaches include latent world models that predict future states, Dyna-style learning from imagined rollouts, and model-predictive control or tree search; Bayesian models and ensembles help represent uncertainty, while control barriers and other safety methods constrain actions. Methods are tested on suites such as DeepMind Control, MuJoCo, Atari, and D4RL, as well as robotic manipulation, autonomous driving, and other physical systems, alongside theoretical work on regret and sample complexity. The central tension is that imagined experience can make learning more efficient, but model errors may accumulate over long horizons or be exploited by the policy, so reliable uncertainty estimates, safe planning, and transfer to real systems remain open challenges.

Latest papers

CardsList

245 papers32 papers in the last four weeks, up 10% on the four weeks before. 0.2% of all new papers.

  1. Toward Safe Autonomous Robotic Endovascular Interventions using World Models

    Apr 22, 2026Harry Robertshaw, Nikola Fischer, Han-Ru Wu +6World Models for RoboticsRobotic Endovascular Intervention

    Surgical & Interventional Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, UK · Department of Radiology, National Taiwan University Hospital, Taiwan · Department of Neuroradiology, King’s College Hospital, UK

  2. Efficient Reinforcement Learning using Linear Koopman Dynamics for Nonlinear Robotic Systems

    Apr 21, 2026Wenjian Hao, Yuxuan Fang, Zehui Lu +1Robotic ControlReinforcement Learning

    School of Aeronautics and Astronautics, Purdue University, West Lafayette, IN 47907, USA · independent researcher

  3. CSLE: A Reinforcement Learning Platform for Autonomous Security Management

    Apr 16, 2026Kim HammarReinforcement LearningAutonomous Cyber Defense

    Division of Network and Systems Engineering, KTH Royal Institute of Technology, Sweden

  4. Learning Ad Hoc Network Dynamics via Graph-Structured World Models

    Apr 16, 2026Can Karacelebi, Yusuf Talha Sahin, Elif Surer +1World Model LearningWorld Models

    Department of Computer Engineering, Middle East Technical University, Ankara, Turkiye · Türk Telekom, Ankara, Turkiye · Graduate School of Informatics, Middle East Technical University, Ankara, Turkiye

  5. Model-Based Reinforcement Learning Exploits Passive Body Dynamics for High-Performance Biped Robot Locomotion

    Apr 16, 2026Tomoya Kamimura, Haruka Washiyama, Akihito SanoRobot LocomotionRL for Legged Locomotion

    Department of Mechanical Science and Bioengineering, Graduate School of Engineering and Science, The University of Osaka, Toyonaka, Japan. · Department of ElectricalTechnology,and MechanicalAichi,Engineering,Japan. Nagoya Institute of

  6. Optimistic Policy Learning under Pessimistic Adversaries with Regret and Violation Guarantees

    Apr 15, 2026Sourav Ganguly, Kartik Pandit, Arnob GhoshAdversarial MARLReinforcement Learning

    Dept. of Electrical and Computer Engineering, NJIT, Newark, NJ, USA

  7. Advantage-Guided Diffusion for Model-Based Reinforcement Learning

    Apr 10, 2026Daniele Foffano, Arvid Eriksson, David Broman +2Model-Based RLDiffusion Model Guidance

    Division of Decision and Control Systems of the EECS School at KTH Royal Institute of Technology, Stockholm, Sweden. · Digital Futures · Division of Software and Computer Systems of the EECS School at KTH Royal Institute of Technology, Stockholm, Sweden.

  8. WOMBET: World Model-Based Experience Transfer for Robust and Sample-efficient Reinforcement Learning

    Apr 10, 2026Mintae Kim, Koushil SreenathReinforcement LearningSample-Efficient RL

    Hybrid Robotics, UC Berkeley Berkeley, CA 94720, USA

  9. RAMP: Hybrid DRL for Online Learning of Numeric Action Models

    Apr 9, 2026Yarin Benyamin, Argaman Mordoch, Shahaf S. Shperberg +1Model-Based RLModel-Based Planning

    Ben-Gurion University of the Negev, Be’er Sheva, Israel

  10. GIRL: Generative Imagination Reinforcement Learning via Information-Theoretic Hallucination Control

    Apr 8, 2026Prakul Sunil HiremathModel-Based RLWorld Models

    Department of Computer Science and Engineering, Visvesvaraya Technological University (VTU), Belagavi, India · Aliens on Earth (AoE) Autonomous Research Group, Belagavi, India

  11. Cross-fitted Proximal Learning for Model-Based Reinforcement Learning

    Apr 6, 2026Nishanth Venkatesh, Andreas A. MalikopoulosCross-FittingReinforcement Learning

    Department of Systems Engineering, Cornell University, Ithaca, NY, USA · Applied Mathematics, Systems Engineering, Mechanical Engineering, Electrical & Computer Engineering, and School of Civil & Environmental Engineering, Cornell University, Ithaca, NY, USA

  12. ReinVBC: A Model-based Reinforcement Learning Approach to Vehicle Braking Controller

    Apr 6, 2026Haoxin Lin, Junjie Zhou, Daheng Xu +1RL ControlModel-Based RL

    National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China · School of Artificial Intelligence, Nanjing University, Nanjing, China · Polixir Technologies, Nanjing, China

  13. Enhancing sample efficiency in reinforcement-learning-based flow control: replacing the critic with an adaptive reduced-order model

    Apr 5, 2026Zesheng Yao, Zhen-Hua Wan, Canjun Yang +2Sample-Efficient RLModel-Based RL

    School of Mechanical Engineering, Zhejiang University, Hangzhou, PR China · Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, 117575 Singapore · Department of Modern Mechanics, University of Science and Technology of China, Hefei 230027, PR China

  14. Learning Task-Invariant Properties via Dreamer: Enabling Efficient Policy Transfer for Quadruped Robots

    Apr 3, 2026Junyang Liang, Yuxuan Liu, Yabin Chang +5Sim-to-Real TransferRobot Policy Adaptation

    Shenzhen University, Shenzhen, China · Peng Cheng Laboratory, Shenzhen, China

  15. Model-Based Reinforcement Learning for Control under Time-Varying Dynamics

    Apr 2, 2026Klemens Iten, Bruce Lee, Chenhao Li +3RL ControlNon-Stationary RL

    ETH Zürich, Rämistrasse 101, 8092 Zürich, Switzerland · ETH AI Center at ETH Zürich

  16. Soft MPCritic: Value-Based Reinforcement Learning for Non-Differentiable Predictive Control

    Apr 1, 2026Thomas Banker, Nathan P. Lawrence, Ali MesbahModel Predictive ControlModel-Based RL

    Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA 94720, USA.

  17. Model-Based Learning of Near-Optimal Finite-Window Policies in POMDPs

    Apr 1, 2026Philip Jordan, Maryam KamgarpourPartially Observable Markov Decision ProcessesPolicy Learning

    SYCAMORE group, Institute of Mechanical Engineering, EPFL Switzerland.

  18. Focal plane wavefront control with model-based reinforcement learning

    Apr 1, 2026Jalo Nousiainen, Iremsu Taskin, Markus Kasper +2RL ControlModel-Based RL

    European Southern Observatory (ESO), Karl-Schwarzschild-Str. 2, 85748 Garching, Germany · STAR Institute, Université de Liège, Allée du Six Août 19C, 4000 Liège, Belgium

  19. A Pontryagin Method of Model-based Reinforcement Learning via Hamiltonian Actor-Critic

    Mar 30, 2026Chengyang Gu, Yuxin Pan, Hui Xiong +1Model-Based RLActor-Critic Methods

    Information Hub, HKUST (Guangzhou), Guangzhou, China · the Department of Computer Science, City University of Hong Kong, Hong Kong, China · the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada

  20. Enhancing Policy Learning with World-Action Model

    Mar 30, 2026Yuci Han, Alper YilmazRobot Policy LearningWorld Action Models

    Photogrammetry and Computer Vision Lab, The Ohio State University, Columbus, OH 43210, USA.

  21. Cost-Matching Model Predictive Control for Efficient Reinforcement Learning in Humanoid Locomotion

    Mar 30, 2026Wenqi Cai, Kyriakos G. Vamvoudakis, Sébastien Gros +1Humanoid Robot LocomotionModel Predictive Control

    Electrical Engineering Program, New York University Abu Dhabi (NYUAD), 129188, UAE. · School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA 30332, United States. · Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.

  22. SkyNet: Belief-Aware Planning for Partially-Observable Stochastic Games

    Mar 29, 2026Adam HailePartially Observable Stochastic GamesImperfect-Information Games

    Dwight and Dian Diercks School of Advanced Computing Milwaukee School of Engineering 1025 N Broadway St, Milwaukee, WI 53202

  23. DreamerAD: Efficient Reinforcement Learning via Latent World Model for Autonomous Driving

    Mar 25, 2026Pengxuan Yang, Yupeng Zheng, Deheng Qian +11RL for Autonomous DrivingLatent World Models

    Institute of Automation, CAS · Chongqing Chang’an Technology Co., Ltd · School of Advanced Interdisciplinary Sciences, UCAS +1

  24. Knowledge-Guided Manipulation Using Multi-Task Reinforcement Learning

    Mar 25, 2026Aditya Narendra, Mukhammadrizo Maribjonov, Dmitry Makarov +2Robotic ManipulationMulti-Task Robotic Manipulation

    MIRAI, Moscow, Russia and MBZUAI, Abu Dhabi, UAE · MIRAI, Moscow, Russia and Innopolis University, Russia · MIRAI, Moscow, Russia +1

  25. Neural ODE and SDE Models for Adaptation and Planning in Model-Based Reinforcement Learning

    Mar 24, 2026Chao Han, Stefanos Ioannou, Luca Manneschi +4Model-Based RLLatent Dynamics Modeling

    School of Computer Science, The University of Sheffield, UK · Cancer Research UK National Biomarker Centre, The University of Manchester, UK · School of Chemical, Materials and Biological Engineering, The University of Sheffield, UK +2

  26. Inference Time Policy Optimization for Offline RL with Differentiable World Models

    Mar 23, 2026Rohan Deb, Stephen J. Wright, Arindam BanerjeeInference-Time OptimizationOffline RL

    Siebel School of Computing and Data Science, Department of Computer Sciences, University of Illinois Urbana-Champaign · University of Wisconsin Madison

  27. Human-Inspired Pavlovian and Instrumental Learning for Autonomous Agent Navigation

    Mar 23, 2026Jingfeng Shan, Francesco Guidi, Mehrdad Saeidi +8Reinforcement LearningModel-Based RL

    WiLab, University of Bologna, via dell’Università 50, 47521 Cesena, Italy · National Research Council of Italy (CNR), viale del Risorgimento 2, 40136 Bologna, Italy · University of Bologna, Department of Psychology “Renzo Canestrari”, 47521 Cesena, Italy

  28. Towards Practical World Model-based Reinforcement Learning for Vision-Language-Action Models

    Mar 21, 2026Zhilong Zhang, Haoxiang Ren, Yihao Sun +6RL for VLMsVision-Language-Action Models

    National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China · School of Artificial Intelligence, Nanjing University, Nanjing, China · Mila - Quebec AI Institute +1

  29. Learn for Variation: Efficient AAV Trajectory Learning through a Differentiable Wireless World Model

    Mar 19, 2026Xiucheng Wang, Zhenye Chen, Nan Cheng +2UAV Trajectory OptimizationModel-Based RL

    State Key Laboratory of ISN and School of Telecommunications Engineering, Xidian University, Xi’an 710071, China · School of Aerospace Science and Technology, Xidian University, Xi’an 710071, China · Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, N2L 3G1, Canada

  30. AcceRL: A Distributed Asynchronous Reinforcement Learning and World Model Framework for Vision-Language-Action Models

    Mar 19, 2026Chengxuan Lu, Shukuan Wang, Yanjie Li +10World Models for VLA ModelsAsynchronous RL

    IROOTECH TECHNOLOGY Wolf 1069 b Lab, Sany Group