Multi-Agent Coordination

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Overview

Multi-agent coordination studies how agents with partial information, different capabilities, or competing incentives can act together in settings such as robot teams, traffic networks, resource allocation, and language-model workflows. Common approaches include decentralized and centralized multi-agent reinforcement learning, game-theoretic planning, role and task assignment, and communication through messages, shared memory, or learned coordination policies. Recent work also develops orchestration protocols and benchmarks for language-model agents, measuring not just task success but information use, role adherence, safety, and coordination failures. A central tension is that communication and additional agents can improve complex teamwork but also introduce overhead, propagate errors, or make performance worse; individual reasoning ability alone does not guarantee effective cooperation.

Latest papers

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520 papers84 papers in the last four weeks, up 91% on the four weeks before. 0.5% of all new papers.

  1. ABSTRAL: Automatic Design of Multi-Agent Systems Through Iterative Refinement and Topology Optimization

    Mar 24, 2026Weijia Song, Jiashu Yue, Zhe PangMulti-Agent SystemsMulti-Agent LLM Systems

  2. Collision-Free Velocity Scheduling for Multi-Agent Systems on Predefined Routes via Inexact-Projection ADMM

    Mar 23, 2026Seungyeop Lee, Jong-Han KimMulti-Agent CoordinationCollision Avoidance

    Department of Aerospace Engineering and the Program in Aerospace Systems Convergence, Inha University, Incheon, South Korea. · Aerospace Systems Research Institute, Inha University, Incheon, South Korea.

  3. Effective Strategies for Asynchronous Software Engineering Agents

    Mar 23, 2026Jiayi Geng, Graham NeubigMulti-Agent CoordinationSoftware Engineering Agents

    Carnegie Mellon University, Language Technologies Institute

  4. Beyond Scalar Rewards: Dense Feedback for LLM Policy Synthesis in Sequential Social Dilemmas

    Mar 19, 2026Víctor GallegoSocial DilemmasMulti-Agent Coordination

    Komorebi AI Technologies, Spain

  5. In Trust We Survive: Emergent Trust Learning

    Mar 18, 2026Qianpu Chen, Giulio Barbero, Mike Preuss +1Multi-Agent CoordinationMulti-Agent Systems

    LIACS, Leiden Institute of Advanced Computer Science, Universiteit Leiden, The Netherlands

  6. Distributed Equilibrium-Seeking in Target Coverage Games via Self-Configurable Networks under Limited Communication

    Mar 18, 2026Jayanth Bhargav, Zirui Xu, Vasileios Tzoumas +2Multi-Agent CoordinationNash Equilibrium Computation

    Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907 USA · Department of Aerospace Engineering, University of Michigan, Ann Arbor, MI 48109 USA

  7. Adaptive Theory of Mind for LLM-based Multi-Agent Coordination

    Mar 17, 2026Chunjiang Mu, Ya Zeng, Qiaosheng Zhang +6Multi-Agent CoordinationMulti-Agent Systems

    School of Cybersecurity, Northwestern Polytechnical University · Shanghai Artificial Intelligence Laboratory · Huawei Noah’s Ark Lab +2

  8. EcoFair-CH-MARL: Scalable Constrained Hierarchical Multi-Agent RL with Real-Time Emission Budgets and Fairness Guarantees

    Mar 15, 2026Saad AlqithamiConstrained MARLMulti-Agent Reinforcement Learning

    Computer Science Department, Al-Baha University, Albaha 65779, Saudi Arabia

  9. Autonomous Agents Coordinating Distributed Discovery Through Emergent Artifact Exchange

    Mar 15, 2026Fiona Y. Wang, Lee Marom, Subhadeep Pal +4Autonomous Scientific DiscoveryAutonomous Research Agents

    Laboratory for Atomistic and Molecular Mechanics (LAMM), Massachusetts Institute of Technology, Cambridge, MA 02139, USA · Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA · Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA +3

  10. LLM Constitutional Multi-Agent Governance

    Mar 13, 2026J. de Curtò, I. de ZarzàAI Agent GovernanceMulti-Agent Systems

    Department of Computer Applications in Science & Engineering, BARCELONA Supercomputing Center, 08034 Barcelona, Spain · Escuela Técnica Superior de Ingeniería (ICAI), Universidad Pontificia Comillas, 28015 Madrid, Spain · Human Centered AI, Data & Software, LUXEMBOURG Institute of Science and Technology, L-4362 Esch-sur-Alzette, Luxembourg

  11. Semantic Consensus: Process-Aware Conflict Detection and Resolution for Enterprise Multi-Agent LLM Systems

    Mar 13, 2026Vivek AcharyaMulti-Agent CoordinationMulti-Agent Consensus

    Independent Researcher, Dallas, TX, USA

  12. JCAS-MARL: Joint Communication and Sensing UAV Networks via Resource-Constrained Multi-Agent Reinforcement Learning

    Mar 13, 2026Islam Guven, Mehmet ParlakIntegrated Sensing and CommunicationWireless Resource Allocation

    ICTEAM, Université catholique de Louvain Ottignies-Louvain-la-Neuve, Belgium

  13. Joint Optimization of Multi-agent Memory System

    Mar 13, 2026Wenyu Mao, Haoyang Liu, Haosong Tan +4Memory-Augmented Language Model AgentsMulti-Agent System Optimization

    University of Science and Technology of China · Institute of Dataspace, Hefei Comprehensive National Science Center

  14. Increasing intelligence in AI agents can worsen collective outcomes

    Mar 12, 2026Neil F. JohnsonMulti-Agent Resource AllocationMulti-Agent Coordination

    Dynamic Online Networks Laboratory and Physics Department, George Washington University, Washington D.C. 20052, USA

  15. 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

  16. Hybrid Human-Agent Social Dilemmas in Energy Markets

    Mar 12, 2026Isuri Perera, Frits de Nijs, Julian GarciaMulti-Agent CoordinationHuman-AI Interaction

    Department of Data Science and AI, Faculty of Information Technology Monash University, Melbourne, Australia

  17. Feedback-Coupled Memory Systems: A Dynamical Model for Adaptive Coordination

    Mar 12, 2026Stefano GrassiCritical Slowing DownMulti-Agent Coordination

    Bangkok University, Phahonyothin Rd, Khlong Nueng, Khlong Luang District, Pathum Thani 12120, Thailand

  18. Decoupling Geometric Planning and Execution in Scalable Multi-Agent Path Finding

    Mar 11, 2026Fernando Salanova, Eduardo Montijano, Cristian MahuleaMulti-Agent PlanningMulti-Agent Path Finding

    Dept. of Systems Engineering and Computer Science, University of Zaragoza, Zaragoza, Spain

  19. UAV-MARL: Multi-Agent Reinforcement Learning for Time-Critical and Dynamic Medical Supply Delivery

    Mar 11, 2026Islam Guven, Mehmet ParlakMulti-Agent CoordinationMulti-Agent Reinforcement Learning

    ICTEAM, Université catholique de Louvain Ottignies-Louvain-la-Neuve, Belgium

  20. 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

  21. TeamHOI: Learning a Unified Policy for Cooperative Human-Object Interactions with Any Team Size

    Mar 9, 2026Stefan Lionar, Gim Hee LeeHuman-Object InteractionHOI Generation

    Garena · Sea AI Lab · National University of Singapore

  22. The Yerkes-Dodson Curve for AI Agents: Emergent Cooperation Under Environmental Pressure in Multi-Agent LLM Simulations

    Mar 7, 2026Ivan PasichnykEmergent Behavior in Multi-Agent SystemsMulti-Agent LLM Systems

    WeLabelData Inc.

  23. Conversational Demand Response: Bidirectional Aggregator-Prosumer Coordination through Agentic AI

    Mar 6, 2026Reda El Makroum, Sebastian Zwickl-Bernhard, Lukas Kranzl +1Demand ResponseMulti-Agent Coordination

    Energy Economics Group, TU Wien, Gußhausstraße 25–29, Vienna, Austria · Industrial Economics and Technology Management, NTNU, Trondheim, Norway

  24. Agent Hunt: Bounty Based Collaborative Autoformalization With LLM Agents

    Mar 6, 2026Chad E. Brown, Cezary Kaliszyk, Josef UrbanAutoformalizationMulti-Agent Collaboration

    AI4REASON · University of Melbourne · AI4REASON, University of Gothenburg and Chalmers University of Technology

  25. The Coordination Gap: Multi-Agent Alternation Metrics for Temporal Fairness in Repeated Games

    Mar 6, 2026Nikolaos Al. Papadopoulos, Ismael Tito Freire, Marti Sanchez-Fibla +1Multi-Agent CoordinationGame Theory

    Department of Applied Informatics, University of Macedonia, Egnatia 156, Thessaloniki 54636, Greece · Institut des Systèmes Intelligents et de Robotique (ISIR), Sorbonne Université, Paris, France · Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain

  26. S5-SHB Agent: Society 5.0 enabled Multi-model Agentic Blockchain Framework for Smart Home

    Mar 5, 2026Janani Rangila, Akila Siriweera, Incheon Paik +3AI Agent GovernanceInternet of Things

    KD University, Colombo, Sri Lanka · University of Aizu, Fukushima, Japan

  27. HiMAP-Travel: Hierarchical Multi-Agent Planning for Long-Horizon Constrained Travel

    Mar 5, 2026The Viet Bui, Wenjun Li, Yong LiuTravel PlanningLong-Horizon LLM Agents

    Singapore Management University

  28. Distributed State Estimation for Vision-Based Cooperative Slung Load Transportation in GPS-Denied Environments

    Mar 4, 2026Jack R. Pence, Jackson Fezell, Jack W. Langelaan +1Aerial RoboticsRelative Pose Estimation

    The Pennsylvania State University, University Park, Pennsylvania, 16802

  29. Learning Approximate Nash Equilibria in Cooperative Multi-Agent Reinforcement Learning via Mean-Field Subsampling

    Mar 4, 2026Emile Anand, Ishani KarmarkarMean-Field MARLReinforcement Learning

    Georgia Institute of Technology, Atlanta, GA · Stanford University, Palo Alto, CA

  30. Benchmarking Emergent Coordination in Large-Scale LLM Populations: An Evaluation Framework on the MoltBook Archive

    Mar 3, 2026Brandon Yee, Pairie KohMulti-Agent CoordinationLLM Agent Evaluation

    Management Lab, Yee Collins Research Group