Multi-Agent Reinforcement Learning

Also known as MARL

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Overview

Multi-agent reinforcement learning studies how multiple decision-makers learn when each agent’s actions affect both the environment and other agents, across cooperative, competitive, and mixed-motive settings. Common approaches include centralized training with decentralized execution, independent or shared actor-critic policies, value factorization such as QMIX, self-play and game-solving methods, and graph-based communication or hierarchical policies. Researchers test these methods in benchmarks such as SMAC, MPE, Overcooked, and multi-agent MuJoCo, and apply them to robotics, traffic, wireless networks, energy systems, and language-agent workflows. A central challenge is scaling coordination and credit assignment while keeping learning stable under non-stationarity and policies robust, safe, and fair with unfamiliar partners and conditions.

Latest papers

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373 papers47 papers in the last four weeks, up 81% on the four weeks before. 0.3% of all new papers.

  1. Federated Multi Agent Deep Learning and Neural Networks for Advanced Distributed Sensing in Wireless Networks

    Feb 24, 2026Nadine Muller, Stefano DeRosa, Su Zhang +1Multi-Agent Reinforcement LearningMulti-Agent Systems

    Faculty of Information Technology and Electrical Engineering, University of Oulu

  2. Descent-Guided Policy Gradient for Scalable Cooperative Multi-Agent Learning

    Feb 23, 2026Shan Yang, Yang LiuCooperative MARLMulti-Agent Reinforcement Learning

    National University of Singapore

  3. Safe Multi-Agent Deep Reinforcement Learning for Privacy-Aware Edge-Device Collaborative DNN Inference

    Feb 23, 2026Hong Wang, Xuwei Fan, Zhipeng Cheng +4Constrained MARLEfficient Neural Network Inference

    School of Future Science and Engineering, Soochow University, Suzhou 215006, China · College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China · School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China +2

  4. Characterizing MARL for Energy Control: A Multi-KPI Benchmark on the CityLearn Environment

    Feb 22, 2026Aymen Khouja, Imen Jendoubi, Oumayma Mahjoub +4Multi-Agent Reinforcement LearningDecentralized MARL

    InstaDeep

  5. Carbon-aware decentralized dynamic task offloading in MIMO-MEC networks via multi-agent reinforcement learning

    Feb 21, 2026Mubshra Zulfiqar, Muhammad Ayzed Mirza, Basit QureshiComputation OffloadingCarbon-Aware Computing

    School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, 430000, Hubei, China · School of Computer Science and Information Engineering, Qilu Institute of Technology, Jinan, 250200, Shandong, China · Department of Computer Science, Prince Sultan University, Riyadh, 12435, Riyadh Province, Saudi Arabia

  6. Toward AI Autonomous Navigation for Mechanical Thrombectomy using Hierarchical Modular Multi-agent Reinforcement Learning (HM-MARL)

    Feb 20, 2026Harry Robertshaw, Nikola Fischer, Lennart Karstensen +6Robotic Endovascular InterventionMulti-Agent Reinforcement Learning

    School of Biomedical Engineering & Imaging Sciences, Kings College London, London, UK · School of Engineering & Materials Science, Queen Mary University of London, London, UK

  7. Diffusing to Coordinate: Efficient Online Multi-Agent Diffusion Policies

    Feb 20, 2026Zhuoran Li, Hai Zhong, Xun Wang +3Multi-Agent Reinforcement LearningMulti-Agent Coordination

    Institute for Interdisciplinary Information Sciences, Tsinghua University · ByteDance

  8. 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.

  9. Safe Continuous-time Multi-Agent Reinforcement Learning via Epigraph Form

    Feb 19, 2026Xuefeng Wang, Lei Zhang, Henglin Pu +2Multi-Agent Reinforcement LearningContinuous-Time RL

    Purdue University

  10. Spatio-temporal dual-stage hypergraph MARL for human-centric multimodal corridor traffic signal control

    Feb 19, 2026Xiaocai Zhang, Neema Nassir, Milad HaghaniTraffic Signal ControlMulti-Agent Reinforcement Learning

    Department of Infrastructure Engineering, Faculty of Engineering and Information Technology, The University of Melbourne, VIC 3010, Australia

  11. Retaining Suboptimal Actions to Follow Shifting Optima in Multi-Agent Reinforcement Learning

    Feb 19, 2026Yonghyeon Jo, Sunwoo Lee, Seungyul HanCooperative MARLMulti-Agent Reinforcement Learning

    Graduate School of Artificial Intelligence, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea 44919

  12. A Unified Framework for Locality in Scalable MARL

    Feb 19, 2026Sourav Chakraborty, Amit Kiran Rege, Claire Monteleoni +1Multi-Agent Reinforcement LearningAverage-Reward RL

    University of Colorado, Boulder, USA. · INRIA Paris, France.

  13. Discovering Multiagent Learning Algorithms with Large Language Models

    Feb 18, 2026Zun Li, John Schultz, Daniel Hennes +1Counterfactual Regret MinimizationMulti-Agent Reinforcement Learning

    Google DeepMind

  14. A Scalable Approach to Solving Simulation-Based Network Security Games

    Feb 18, 2026Michael Lanier, Yevgeniy VorobeychikMulti-Agent Reinforcement LearningHierarchical RL

  15. 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

  16. CAFE: Causally-Guided Automated Feature Engineering with Multi-Agent Reinforcement Learning

    Feb 18, 2026Arun Vignesh Malarkkan, Wangyang Ying, Yanjie FuAutomated Feature EngineeringDistribution Shift Robustness

    School of Computing, Arizona State University

  17. Multi-Modal Multi-Agent Reinforcement Learning for Radiology Report Generation

    Feb 17, 2026Kaito Baba, Risa Kishikawa, Satoshi KoderaRadiology Report GenerationMultimodal Agents

    Department of Cardiovascular Medicine The University of Tokyo Hospital, Tokyo, Japan

  18. Fairness over Equality: Correcting Social Incentives in Asymmetric Sequential Social Dilemmas

    Feb 17, 2026Alper Demir, Hüseyin Aydın, Kale-ab Abebe Tessera +2Cooperative MARLMulti-Agent Reinforcement Learning

    Izmir University of Economics & University of Edinburgh, Izmir, Turkey · Middle East Technical University & Utrecht University, Ankara, Turkey · University of Edinburgh, Edinburgh, United Kingdom +1

  19. Fluid-Agent Reinforcement Learning

    Feb 16, 2026Shishir Sharma, Doina Precup, Theodore J. PerkinsMulti-Agent Reinforcement LearningMulti-Agent Coordination

    Mila – Quebec Artificial Intelligence Institute, Montreal, Canada · McGill University, Montreal, Canada · Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Canada

  20. Dr. MAS: Stable Reinforcement Learning for Multi-Agent LLM Systems

    Feb 9, 2026Lang Feng, Longtao Zheng, Shuo He +2Multi-Agent LLM SystemsMulti-Agent System Optimization

    Nanyang Technological University, Singapore

  21. Flow Matching for Offline Reinforcement Learning with Discrete Actions

    Feb 5, 2026Fairoz Nower Khan, Nabuat Zaman Nahim, Ruiquan Huang +2Markov ChainsReinforcement Learning

    Department of Computer Science, University of Kentucky · Department of Computing and Information Sciences, Rochester Institute of Technology

  22. Explicit Credit Assignment through Local Rewards and Dependence Graphs in Multi-Agent Reinforcement Learning

    Jan 29, 2026Bang Giang Le, Viet Cuong TaCredit Assignment in RLCredit Assignment

    Human-Machine Interaction Laboratory VNU University of Engineering and Technology, Hanoi, Vietnam

  23. Does Centralized Learning Help Embodied Agents Coordinate, and When Can a Tabular Study Tell?

    Jan 24, 2026Muhammad Ahmed Atif, Nehal Naeem Haji, Muhammad Ebad Atif +1Multi-Agent Reinforcement LearningCooperative MARL

    Dhanani School of Science and Technology, Habib University, Karachi, Pakistan

  24. HiDVFS: Hierarchical Multi-Agent DVFS for Real-Time OpenMP DAG Workloads

    Jan 10, 2026Mohammad Pivezhandi, Abusayeed Saifullah, Ali JannesariReal-Time SchedulingMulti-Agent Reinforcement Learning

    Department of Computer Science Wayne State University, Detroit, MI, USA · Department of Computer Science University of Texas at Dallas, Richardson, TX, USA · Department of Computer Science Iowa State University, Ames, IA, USA

  25. UBCL: A Reinforcement Learning Framework for Controllable and Diverse Player Behaviors

    Dec 11, 2025Atahan Cilan, Atay ÖzgövdeReinforcement LearningHuman Behavior Simulation

    Turkish Aerospace, Istanbul, Turkey · Department of Computer Engineering, Boğaziçi University, Istanbul, Turkey

  26. Transformer-Based Multi-Agent Reinforcement Learning for Networked Systems with Long-Range Interactions

    Nov 17, 2025Vidur Sinha, Muhammed Ustaomeroglu, Guannan QuCounterfactual Credit AssignmentGraph Transformer

    Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, USA

  27. A Quantitative Comparison of Centralised and Distributed Reinforcement Learning-Based Control for Soft Robotic Arms

    Nov 4, 2025Linxin Hou, Qirui Wu, Zhihang Qin +3RL ControlRobotic Policy Evaluation

    Department of Electrical and Computer Engineering, National University of Singapore · Department of Computer Science, National University of Singapore · Department of Mechanical Engineering, National University of Singapore

  28. LLM-Empowered Agentic MAC Protocols: A Dynamic Stackelberg Game Approach

    Oct 13, 2025Renxuan Tan, Rongpeng Li, Fei Wang +4Agentic RLStackelberg Games

    College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China · Huawei Technologies Company Ltd., Shanghai 210026, China · Zhejiang Lab as well as Zhejiang University, Hangzhou 310027, China +1

  29. Climate Surrogates for Scalable Multi-Agent Reinforcement Learning: A Case Study with CICERO-SCM

    Oct 9, 2025Oskar Bohn Lassen, Serio Angelo Maria Agriesti, Filipe Rodrigues +2Neural Surrogate ModelingSurrogate Modeling

    Technical University of Denmark Kongens Lyngby, Denmark

  30. Game-Theoretic Understandings of Multi-Agent Systems with Multiple Objectives

    Sep 27, 2025Zixin Lin, Qianyi Tan, Sihong He +1Game TheoryMulti-Objective Reinforcement Learning

    Department of Electrical and Computer Engineering, Department of Computer Science, University of Central Florida, Orlando, FL 32816