Decentralized MARL

MARL: Multi-Agent Reinforcement Learning

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Overview

Decentralized multi-agent reinforcement learning (MARL) studies how agents can coordinate when each acts on local observations rather than relying on a central controller with complete system information. Common approaches include independent policy or value learning, centralized training with decentralized execution, parameter sharing, graph-based message passing, and distillation of centralized experts; theory also uses potential games, consensus, and regret analysis to establish learning guarantees. Work spans benchmarks such as SMAC and MPE as well as robotics, traffic control, energy networks, and wireless resource allocation, with increasing attention to safety, changing team sizes, and limited communication. A central tension is that local policies can scale and tolerate failures, yet coordination, credit assignment, and global safety are difficult without richer communication or centralized training—and those supports can undermine the autonomy decentralization is meant to provide.

Latest papers

CardsList

122 papers16 papers in the last four weeks, up 14% on the four weeks before. 0.1% of all new papers.

  1. CoordLight: Learning Decentralized Coordination for Network-Wide Traffic Signal Control

    Mar 25, 2026Yifeng Zhang, Harsh Goel, Peizhuo Li +3Traffic Signal ControlMulti-Agent Coordination

    Department of Mechanical Engineering, National University of Singapore · Chandra Department of Electrical and Computer Engineering, The University of Texas at Austin · Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology

  2. Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning

    Mar 25, 2026Yude Li, Zhexuan Zhou, Huizhe Li +6Multi-Agent SystemsMulti-Robot Coordination

    The authors are with the School of Intelligence Science and Engineering, the Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics, and the Shenzhen Key Lab for Advanced Motion Control and Modern Automation Equipments, Harbin Institute of Technology, Shenzhen, Guangdong 518055, China

  3. Dual-Graph Multi-Agent Reinforcement Learning for Handover Optimization

    Mar 25, 2026Matteo Salvatori, Filippo Vannella, Sebastian Macaluso +5Wireless CommunicationsDecentralized MARL

    Telefónica Research, Barcelona, 08019, Spain · Innocube PC, 55534 Thessaloniki, Greece · Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi, 67100, Greece

  4. Safe Decentralized Operation of EV Virtual Power Plant with Limited Network Visibility via Multi-Agent Reinforcement Learning

    Mar 24, 2026Chenghao Huang, Jiarong Fan, Weiqing Wang +1Power SystemsDecentralized MARL

    Department of Data Science and AI, Faculty of IT, Monash University, Australia · Monash Energy Institute, Monash University, Australia

  5. Partial Attention in Deep Reinforcement Learning for Safe Multi-Agent Control

    Mar 23, 2026Turki Bin Mohaya, Peter SeilerRL for Autonomous DrivingMulti-Agent Reinforcement Learning

    Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA.

  6. Communication-Aware Multi-Agent Reinforcement Learning for Decentralized Cooperative UAV Deployment

    Mar 17, 2026Enguang Fan, Yifan Chen, Zihan Shan +3Cooperative MARLDecentralized MARL

    University of Illinois at Urbana-Champaign · Boeing Research and Technology

  7. Sample-Efficient Hypergradient Estimation for Decentralized Bi-Level Reinforcement Learning

    Mar 16, 2026Mikoto Kudo, Takumi Tanabe, Akifumi Wachi +1Hypergradient OptimizationDecentralized MARL

    University of Tsukuba · RIKEN AIP · LY Corporation

  8. The price of decentralization in managing engineering systems through multi-agent reinforcement learning

    Mar 12, 2026Prateek Bhustali, Pablo G. Morato, Konstantinos G. Papakonstantinou +1Decentralized MARLMulti-Agent Coordination

    Faculty of Architecture and the Built Environment, Delft University of Technology, Delft, 2628 BL, The Netherlands · Engineering Risk Analysis Group, Technical University of Munich, Munich, 80333, Germany · Department of Civil & Environmental Engineering, The Pennsylvania State University, University Park, PA, 16802, USA

  9. Octopus-inspired Distributed Control for Soft Robotic Arms: A Graph Neural Network-Based Attention Policy with Environmental Interaction

    Mar 10, 2026Linxin Hou, Qirui Wu, Zhihang Qin +2Continuum Robot ControlDecentralized MARL

    Department of Electrical and Computer Engineering, National University of Singapore, Singapore · Department of Computer Science, National University of Singapore, Singapore · Department of Mechanical Engineering, National University of Singapore, Singapore +2

  10. Less is More: Robust Zero-Communication 3D Pursuit-Evasion via Representational Parsimony

    Mar 9, 2026Jialin Ying, Zhihao Li, Zicheng Dong +2Multi-Agent SystemsMulti-Agent Coordination

    Department of Automation, Central South University, Changsha, China

  11. DeReCo: Decoupling Representation and Coordination Learning for Object-Adaptive Decentralized Multi-Robot Cooperative Grasping and Lifting

    Mar 9, 2026Kazuki Shibata, Ryosuke Sota, Shandil Dhiresh Bosch +3Multi-Robot Cargo TransportationMulti-Robot Coordination

    All the authors are with the Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology (NAIST), Nara, Japan. · Shandil Dhiresh Bosch is with the Department of Cognitive Robotics, Faculty of Mechanical Engineering, Delft University of Technology, Delft, Netherlands.

  12. Beyond Reward Suppression: Reshaping Steganographic Communication Protocols in MARL via Dynamic Representational Circuit Breaking

    Mar 7, 2026Liu Hung MingAI Agent SafetyAI Agent Auditing

    PARRAWA AI

  13. Reinforcing the World's Edge: A Continual Learning Problem in the Multi-Agent-World Boundary

    Mar 6, 2026Dane MalenfantNon-Stationary RLDecentralized MARL

    School of Computer Science McGill University Mila - The Québec AI Institute

  14. Dual-Interaction-Aware Cooperative Control Strategy for Alleviating Mixed Traffic Congestion

    Mar 4, 2026Zhengxuan Liu, Yuxin Cai, Yijing Wang +3Intelligent Transportation SystemsMulti-Agent Control

    Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System, School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China · School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore · Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China

  15. HALO: Learning Human-Robot Collaboration via Heterogeneous-Agent Lyapunov Policy Optimization

    Mar 4, 2026Hao Zhang, Yaru Niu, Yikai Wang +2Decentralized MARLHeterogeneous MARL

    ETAIC Lab, Department of Electrical Engineering, University of Texas at Arlington, USA · Safe AI Lab, Department of Mechanical Engineering, Carnegie Mellon University, USA.

  16. Principled Learning-to-Communicate with Quasi-Classical Information Structures

    Mar 4, 2026Xiangyu Liu, Haoyi You, Kaiqing ZhangMulti-Agent CommunicationDecentralized MARL

    University of Maryland, College Park, MD, USA, 20742

  17. TSC: Topology-Conditioned Stackelberg Coordination for Multi-Agent Reinforcement Learning in Interactive Driving

    Feb 27, 2026Xiaotong Zhang, Gang Xiong, Yuanjing Wang +3Multi-Agent CoordinationDecentralized MARL

    State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China · School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China · Department of Natural Sciences, University of Durham, Durham DH1 3LE, United Kingdom +4

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

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

  19. 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

  20. 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

  21. HONEST-CAV: Hierarchical Optimization of Network Signals and Trajectories for Connected and Automated Vehicles with Multi-Agent Reinforcement Learning

    Feb 21, 2026Ziyan Zhang, Changxin Wan, Peng Hao +5Intelligent Transportation SystemsTraffic Signal Control

    College of Engineering, Center for Environmental Research and Technology, University of California at Riverside, Riverside, CA, 92507. · InfoTech Labs, Toyota Motor North America, Mountain View, CA, 94043.

  22. Action-Graph Policies: Learning Action Co-dependencies in Multi-Agent Reinforcement Learning

    Feb 19, 2026Nikunj Gupta, James Zachary Hare, Jesse Milzman +2Multi-Agent CoordinationDecentralized MARL

    University of Southern California, Los Angeles, CA, USA · DEVCOM Army Research Laboratory, Adelphi, MD, USA · DEVCOM ARL Army Research Office, Los Angeles, CA, USA.

  23. Learning Distributed Equilibria in Linear-Quadratic Stochastic Differential Games: An αα-Potential Approach

    Feb 18, 2026Philipp Plank, Yufei ZhangGame TheoryNash Equilibrium Computation

    Department of Mathematics, Imperial College London, London, UK

  24. Multi-agent cooperation through in-context co-player inference

    Feb 18, 2026Marissa A. Weis, Maciej Wołczyk, Rajai Nasser +4Cooperative MARLDecentralized MARL

    Google, Paradigms of Intelligence Team · Santa Fe Institute

  25. MARLEM: A Multi-Agent Reinforcement Learning Simulation Framework for Implicit Cooperation in Decentralized Local Energy Markets

    Feb 17, 2026Nelson Salazar-Pena, Alejandra Tabares, Andres Gonzalez-ManceraMulti-Agent CoordinationPower Systems

    Department of Mechanical Engineering, Universidad de los Andes, 111711, Bogotá D.C., Colombia · Department of Industrial Engineering, Universidad de los Andes, 111711, Bogotá D.C., Colombia

  26. Harnessing Implicit Cooperation: A Multi-Agent Reinforcement Learning Approach Towards Decentralized Local Energy Markets

    Feb 17, 2026Nelson Salazar-Pena, Alejandra Tabares, Andres Gonzalez-ManceraMulti-Agent CoordinationDecentralized MARL

    Department of Mechanical Engineering, Universidad de los Andes, 111711, Bogotá D.C., Colombia · Department of Industrial Engineering, Universidad de los Andes, 111711, Bogotá D.C., Colombia

  27. Distributed scalable coupled policy algorithm for networked multi-agent reinforcement learning

    Dec 5, 2025Pengcheng Dai, Dongming Wang, Wenwu Yu +1Cooperative MARLDecentralized MARL

    Engineering Systems and Design Pillar, Singapore University of Technology and Design, Singapore 487372 · Department of Electrical and Computer Engineering, University of California, Riverside, CA 92521, USA · Frontiers Science Center for Mobile Information Communication and Security, School of Mathematics, Southeast University, Nanjing 210096, China, and also with Purple Mountain Laboratories, Nanjing 211102, China

  28. 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

  29. Optimization without Future Compromises? Decentralized Coordination via Collective and Reinforcement Learning

    Sep 22, 2025Chuhao Qin, Evangelos PournarasMulti-Agent System OptimizationMulti-Agent Coordination

    School of Computer Science, University of Leeds, UK

  30. Integrated Noise and Safety Management in UAM via A Unified Reinforcement Learning Framework

    Aug 22, 2025Surya Murthy, Zhenyu Gao, John-Paul Clarke +1Multi-Objective Reinforcement LearningCollision Avoidance

    Graduate Research Assistant, Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin · Postdoctoral Fellow, Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin · Professor and Ernest Cockrell, Jr. Memorial Chair in Engineering, Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin +1