Reinforcement Learning

Also known as RL

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Overview

Reinforcement learning studies how an agent can choose actions over time to earn rewards, using experience to improve its decisions. Common approaches include value-based methods such as Q-learning, policy-gradient methods such as PPO, and model-based methods that learn or use a model of the environment; offline and hierarchical methods address learning from fixed data and long tasks. Applications range from Atari and MuJoCo benchmarks to robot control, traffic, games, and language-model agents that use tools or solve multi-step problems. A central challenge is making learning efficient and reliable when rewards are sparse or imperfect, environments change, and success in simulation or benchmarks may not transfer safely to deployment.

Latest papers

CardsList

1,742 papers237 papers in the last four weeks, up 46% on the four weeks before. 1.4% of all new papers.

  1. Sparse Masked Attention Policies for Reliable Generalization

    Feb 23, 2026Caroline Horsch, Laurens Engwegen, Max Weltevrede +2Reinforcement LearningGeneralization in RL

    Department of Intelligent Systems, Delft University of Technology, Delft, Netherlands.

  2. DSDR: Dual-Scale Diversity Regularization for Exploration in LLM Reasoning

    Feb 23, 2026Zhongwei Wan, Yun Shen, Zhihao Dou +9Reinforcement LearningRL for Language Model Reasoning

    The Ohio State University, USA · Case Western Reserve University, USA · The Chinese University of Hong Kong, Hong Kong +4

  3. Decision MetaMamba: Enhancing Selective SSM in Offline RL with Heterogeneous Sequence Mixing

    Feb 23, 2026Wall Kim, Chaeyoung Song, Hanul KimReinforcement LearningOffline RL

    Samsung Electronics, Hwaseong, South Korea · Seoul National University of Science and Technology, Seoul, South Korea

  4. Bellman Value Decomposition for Task Logic in Safe Optimal Control

    Feb 23, 2026William Sharpless, Oswin So, Dylan Hirsch +2Safe RLReinforcement Learning

    UCSD · MIT

  5. IR3^3: Contrastive Inverse Reinforcement Learning for Interpretable Detection and Mitigation of Reward Hacking

    Feb 23, 2026Mohammad Beigi, Ming Jin, Junshan Zhang +3Reward HackingReinforcement Learning

    UC Davis · Virginia Tech · Salesforce +1

  6. Hilbert-Augmented Reinforcement Learning for Scalable Multi-Robot Coverage and Exploration

    Feb 23, 2026Tamil Selvan Gurunathan, Aryya GangopadhyayMulti-Robot ExplorationMulti-Robot Systems

  7. How to Allocate, How to Learn? Dynamic Rollout Allocation and Advantage Modulation for Policy Optimization

    Feb 22, 2026Yangyi Fang, Jiaye Lin, Xiaoliang Fu +6Reinforcement LearningRL for Language Model Reasoning

    Meituan · Tsinghua University · Fudan University +1

  8. IDSelect: A RL-Based Cost-Aware Selection Agent for Video-based Multi-Modal Person Recognition

    Feb 22, 2026Yuyang Ji, Yixuan Shen, Kien Nguyen +2Efficient Multimodal InferenceModel Selection

    Department of Computer Science, Drexel University · School of Electrical Engineering and Robotics, Queensland University of Technology · Department of Electrical and Computer Engineerin, Drexel University

  9. Issues with Measuring Task Complexity via Random Policies in Robotic Tasks

    Feb 21, 2026Reabetswe M. Nkhumise, Mohamed S. Talamali, Aditya GilraReinforcement Learning

    University of Sheffield, Sheffield, United Kingdom · Wirtschaftsuniversität, Vienna, Austria

  10. Not all tokens are needed(NAT): token efficient reinforcement learning

    Feb 20, 2026Hejian Sang, Yuanda Xu, Zhengze Zhou +2RL for Language ModelsReinforcement Learning

    LinkedIn Corporation, CA, USA

  11. PRISM: Parallel Reward Integration with Symmetry for MORL

    Feb 20, 2026Finn van der Knaap, Kejiang Qian, Zheng Xu +1Equivariant Policy LearningReinforcement Learning

    University of Edinburgh · Meta Superintelligence Labs.

  12. Mean-Field Reinforcement Learning without Synchrony

    Feb 20, 2026Shan YangMean-Field MARLReinforcement Learning

    Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore.

  13. Flow Actor-Critic for Offline Reinforcement Learning

    Feb 20, 2026Jongseong Chae, Jongeui Park, Yongjae Shin +3Flow-Based Policy LearningConservative RL

    KAIST · UNIST

  14. Learning Optimal and Sample-Efficient Decision Policies with Guarantees

    Feb 20, 2026Daqian ShaoReinforcement LearningSample-Efficient RL

    Wolfson College University of Oxford

  15. Memory-Based Advantage Shaping for LLM-Guided Reinforcement Learning

    Feb 20, 2026Narjes Nourzad, Carlee Joe-WongMemory-Augmented RLReinforcement Learning

    University of Southern California · Carnegie Mellon University

  16. MIRA: Memory-Integrated Reinforcement Learning Agent with Limited LLM Guidance

    Feb 20, 2026Narjes Nourzad, Carlee Joe-WongMemory-Augmented RLReinforcement Learning

    University of Southern California, Electrical and Computer Engineering, Los Angeles, CA 90007, USA · Carnegie Mellon University, Electrical and Computer Engineering, Pittsburgh, PA 15213, USA

  17. Promptable segmentation with region exploration enables minimal-effort expert-level prostate cancer delineation

    Feb 19, 2026Junqing Yang, Natasha Thorley, Ahmed Nadeem Abbasi +4Medical Image SegmentationInteractive Medical Image Segmentation

    UCL Hawkes Institute; Department of Medical Physics and Biomedical Engineering, University College London, UK. · Centre of Medical Imaging, University College London, UK. · Department of Oncology, Aga Khan University Hospital, Pakistan. +1

  18. KLong: Training LLM Agent for Extremely Long-horizon Tasks

    Feb 19, 2026Yue LiuLLM Agent TrainingLong-Horizon Agent Tasks

    NUS

  19. LexiSafe: Offline Safe Reinforcement Learning with Lexicographic Safety-Reward Hierarchy

    Feb 19, 2026Hsin-Jung Yang, Zhanhong Jiang, Prajwal Koirala +3Reinforcement LearningSafe RL

    Dept. of Mechanical Engineering Iowa State University Ames, USA · Translational AI Center Iowa State University Ames, USA · Sibley School of Mechanical and Aerospace Engineering Cornell University Ithaca, USA

  20. RLGT: A reinforcement learning framework for extremal graph theory

    Feb 19, 2026Ivan Damnjanović, Uroš Milivojević, Irena Đorđević +1Reinforcement LearningRL for Combinatorial Optimization

    Faculty of Electronic Engineering, University of Niš, Aleksandra Medvedeva 4, Niš, 18104, Serbia · Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, Koper, 6000, Slovenia · College of Integrative Studies, Abdullah Al Salem University, Firdous Street, Block 3, Khaldiya, 72303, Kuwait

  21. Phase-Aware Mixture of Experts for Agentic Reinforcement Learning

    Feb 19, 2026Shengtian Yang, Yu Li, Shuo He +4Reinforcement LearningRL for LLM Agents

    School of Computer Science and Engineering, Southeast University, Nanjing, China · Kuaishou Technology, Beijing, China · College of Computing and Data Science, Nanyang Technological University, Singapore

  22. VAM: Verbalized Action Masking for Controllable Exploration in RL Post-Training -- A Chess Case Study

    Feb 18, 2026Zhicheng Zhang, Ziyan Wang, Yali Du +1RL for Language ModelsRL Exploration

    Carnegie Mellon University · King’s College London

  23. Multi-Agent Reinforcement Learning for V2X Resource Allocation: Disentangling MARL Challenges Through Benchmarking

    Feb 18, 2026Siyuan Wang, Lei Lei, Pranav Maheshwari +2RL BenchmarksReinforcement Learning

    College of Engineering, University of Guelph, Guelph, Ontario, Canada · College of Electrical Engineering and Computer Sciences, Ningbo University, Ningbo, 315211, China

  24. Graphon Mean-Field Subsampling for Cooperative Heterogeneous Multi-Agent Reinforcement Learning

    Feb 18, 2026Emile Anand, Richard Hoffmann, Sarah Liaw +1Reinforcement LearningCooperative MARL

    School of Computer Science, Georgia Institute of Technology, Atlanta, GA, USA · Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA, USA · Kempner Institute, Harvard University, Cambridge, MA, USA

  25. STAPO: Stabilizing Reinforcement Learning for LLMs by Silencing Rare Spurious Tokens

    Feb 17, 2026Shiqi Liu, Zeyu He, Guojian Zhan +10Reinforcement LearningRL for Language Model Reasoning

    School of Vehicle and Mobility & College of AI, Tsinghua University · Didi Voyager Labs, DiDi Autonomous Driving

  26. Efficient Knowledge Transfer for Jump-Starting Control Policy Learning of Multirotors through Physics-Aware Neural Architectures

    Feb 17, 2026Welf Rehberg, Mihir Kulkarni, Philipp Weiss +1Robotic RLCross-Embodiment Robot Learning

    Department of Engineering Cybernetics at the Norwegian University of Science and Technology, O.S. Bragstads Plass 2D, 7034, Trondheim, Norway

  27. Contextual Intelligence The Next Leap for Reinforcement Learning

    Feb 17, 2026André BiedenkappContextual RLZero-Shot RL

    Albert-Ludwigs-Universität Freiburg, Germany

  28. CDRL: A Reinforcement Learning Framework Inspired by Cerebellar Circuits and Dendritic Computational Strategies

    Feb 17, 2026Sibo Zhang, Rui Jing, Liangfu Lv +2Reinforcement LearningSample-Efficient RL

    Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.

  29. MyoInteract: A Framework for Fast Prototyping of Biomechanical HCI Tasks using Reinforcement Learning

    Feb 16, 2026Ankit Bhattarai, Hannah Selder, Florian Fischer +2Human-Computer InteractionReinforcement Learning

    Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) Dresden/Leipzig, Leipzig University Leipzig, Germany

  30. Interactionless Inverse Reinforcement Learning: A Data-Centric Framework for Durable Alignment

    Feb 16, 2026Elias Malomgré, Pieter SimoensAI AlignmentReinforcement Learning

    IDLab, Ghent University - imec, Ghent, Belgium