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

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

  1. Harmonizing Dense and Sparse Signals in Multi-turn RL: Dual-Horizon Credit Assignment for Industrial Sales Agents

    Mar 2, 2026Haojin Yang, Ai Jian, Xinyue Huang +5RL for LLM AgentsReinforcement Learning

    Peking University · Beijing University of Posts and Telecommunications · Sun Yat-sen University +2

  2. SubstratumGraphEnv: Reinforcement Learning Environment (RLE) for Modeling System Attack Paths

    Mar 2, 2026Bahirah Adewunmi, Edward Raff, Sanjay PurushothamReinforcement LearningAutonomous Cyber Defense

    University of Maryland, Baltimore County · CrowdStrike

  3. PAC Guarantees for Reinforcement Learning: Sample Complexity, Coverage, and Structure

    Mar 1, 2026Joshua SteierFunction Approximation in RLReinforcement Learning

  4. Hybrid TD3: Overestimation Bias Analysis and Stable Policy Optimization for Hybrid Action Space

    Mar 1, 2026Thanh-Tuan Tran, Thanh Nguyen Canh, Nak Young Chong +1Hybrid Action Space RLReinforcement Learning

    University of Engineering and Technology, Vietnam National University, 10000, Hanoi, Vietnam. · School of Information Science, Japan Advanced Institute of Science and Technology, Nomi, 923-1211, Ishikawa, Japan. · Department of Robotics, Hanyang University, Ansan, 15588, Gyeonggi, Korea.

  5. The Informational Cost of Agency: A Bounded Measure of Interaction Efficiency for Deployed Reinforcement Learning

    Mar 1, 2026Wael Hafez, Cameron Reid, Amit NazeriAI Agent ReliabilityReinforcement Learning

    Semarx Research LLC Alexandria, VA, USA.

  6. Intent-Context Synergy Reinforcement Learning for Autonomous UAV Decision-Making in Air Combat

    Mar 1, 2026Jiahao Fu, Feng YangReinforcement LearningPartially Observable RL

    National Elite Institute of Engineering,Northwestern Polytechnical University, Xi’an, Shanxi, China · School of Automation, Northwestern Polytechnical University, Xi’an, Shanxi, China

  7. Stabilizing Policy Optimization via Logits Convexity

    Mar 1, 2026Hongzhan Chen, Tao Yang, Yuhua Zhu +3Policy OptimizationReinforcement Learning

    School of Computer Science and Engineering, Sun Yat-sen University, China · Shanghai Innovation Institute · Wechat Search, Tencent Inc, China +1

  8. Principled Fast and Meta Knowledge Learners for Continual Reinforcement Learning

    Mar 1, 2026Ke Sun, Hongming Zhang, Jun Jin +4Reinforcement LearningContinual RL

    University of Alberta · National Key Laboratory of Cognition and Decision Intelligence for Complex Systems, Institution of Automation, Chinese Academy of Sciences · Edmonton Research Center, Huawei Canada +2

  9. Learning to Attack: A Bandit Approach to Adversarial Context Poisoning

    Feb 28, 2026Ray Telikani, Amir H. GandomiBlack-Box Adversarial AttacksAdversarial Bandits

    Data Science Institute, University of Technology Sydney, NSW, Australia

  10. Multi-Agent Reinforcement Learning for Dynamic Pricing: Balancing Profitability,Stability and Fairness

    Feb 28, 2026Krishna Kumar Neelakanta Pillai Santha Kumari AmmaDynamic PricingReinforcement Learning

  11. Conservative Equilibrium Discovery in Offline Game-Theoretic Multiagent Reinforcement Learning

    Feb 27, 2026Austin A. Nguyen, Michael P. WellmanReinforcement LearningGame Theory

    University of Michigan

  12. Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation

    Feb 27, 2026Tyler Han, Bat Nemekhbold, Siyang Shen +6Robot Learning from VideoReinforcement Learning

    University of Washington

  13. Bridging Dynamics Gaps via Diffusion Schrödinger Bridge for Cross-Domain Reinforcement Learning

    Feb 27, 2026Hanping Zhang, Yuhong GuoReinforcement LearningCross-Domain Transfer Learning

    School of Computer Science, Carleton University, Ottawa, Canada

  14. Truncated Step-Level Sampling with Process Rewards for Retrieval-Augmented Reasoning

    Feb 26, 2026Chris Samarinas, Haw-Shiuan Chang, Hamed ZamaniReinforcement LearningProcess Reward Models

    Center for Intelligent Information Retrieval University of Massachusetts Amherst Amherst, MA, United States

  15. A Model-Free Universal AI

    Feb 26, 2026Yegon Kim, Juho LeeReinforcement LearningBayesian RL

    Graduate School of AI, KAIST, Seoul, South Korea

  16. GeoWorld: Geometric World Models

    Feb 26, 2026Zeyu Zhang, Danning Li, Ian Reid +1World Model LearningWorld Models

    ANU · MBZUAI

  17. Exploratory Memory-Augmented LLM Agent via Hybrid On- and Off-Policy Optimization

    Feb 26, 2026Zeyuan Liu, Jeonghye Kim, Xufang Luo +2RL for LLM AgentsReinforcement Learning

    Microsoft Research · KAIST

  18. Learning to Generate Secure Code via Token-Level Rewards

    Feb 26, 2026Jiazheng Quan, Xiaodong Li, Bin Wang +5Secure Code GenerationRL for Code Generation

    Fuyao University of Science and Technology · Xiamen University · Peking University +1

  19. QSIM: Mitigating Overestimation in Multi-Agent Reinforcement Learning via Action Similarity Weighted Q-Learning

    Feb 26, 2026Yuanjun Li, Bin Zhang, Hao Chen +3Reinforcement LearningCooperative MARL

    Shandong University · The Key Laboratory of Cognition and Decision Intelligence for Complex Systems, Institute of Automation, Chinese Academy of Sciences · Li Auto Inc. +1

  20. Learning Rewards, Not Labels: Adversarial Inverse Reinforcement Learning for Machinery Fault Detection

    Feb 25, 2026Dhiraj Neupane, Richard Dazeley, Mohamed Reda Bouadjenek +1Fault DetectionUnsupervised Anomaly Detection

    Deakin University Waurn Ponds, Victoria, Australia

  21. Enhancing Multi-Modal LLMs Reasoning via Difficulty-Aware Group Normalization

    Feb 25, 2026Jinghan Li, Junfeng Fang, Jinda Lu +5Multimodal Large Language ModelsMultimodal Reasoning

    University of Science and Technology of China · National University of Singapore

  22. 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

  23. GradAlign: Gradient-Aligned Data Selection for LLM Reinforcement Learning

    Feb 25, 2026Ningyuan Yang, Weihua Du, Weiwei Sun +2RL for Language ModelsReinforcement Learning

    Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University · Language Technologies Institute (LTI), Carnegie Mellon University

  24. 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

  25. Regret-Guided Search Control for Efficient Learning in AlphaZero

    Feb 24, 2026Yun-Jui Tsai, Wei-Yu Chen, Yan-Ru Ju +2Reinforcement LearningGame-Playing Agents

    Department of Computer Science, National Yang Ming Chiao Tung University, Taiwan · Institute of Information Science, Academia Sinica, Taiwan · College of Computing, Georgia Institute of Technology

  26. Fuz-RL: A Fuzzy-Guided Robust Framework for Safe Reinforcement Learning under Uncertainty

    Feb 24, 2026Xu Wan, Chao Yang, Cheng Yang +2Safe RLReinforcement Learning

    Zhejiang University · Alibaba DAMO Academy · Peking University

  27. TrajGPT-R: Generating Urban Mobility Trajectory with Reinforcement Learning-Enhanced Generative Pre-trained Transformer

    Feb 24, 2026Jiawei Wang, Chuang Yang, Jiawei Yong +6Trajectory GenerationRL for Generative Models

    The University of Tokyo, Tokyo 113-0034, Japan · Toyota Motor Corporation, Tokyo 112-0004, Japan

  28. 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

  29. Cross domain Persistent Monitoring for Hybrid Aerial Underwater Vehicles

    Feb 23, 2026Ricardo B. Grando, Victor A. Kich, Alisson H. Kolling +3RoboticsUnderwater Robotics

  30. Understanding Gap-Dependent Regret for Optimism-Based Reinforcement Learning with Linear Function Approximation

    Feb 23, 2026Haochen Zhang, Zhong Zheng, Lingzhou XueRegret Minimization in RLReinforcement Learning

    Department of Statistics, The Pennsylvania State University · Department of Applied and Computational Mathematics and Statistics, University of Notre Dame