Multi-Agent Coordination

Ask about this topic

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

CardsList

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

  1. Game-theoretic Regulated Decentralized Coordination for Airspace Sector Overload Mitigation

    Nov 14, 2025Jaehan Im, Daniel Delahaye, David Fridovich-Keil +1Multi-Agent CoordinationAir Traffic Management

    The University of Texas at Austin, 110 Inner Campus Drive, Austin, 78712, Texas, United States · École Nationale de lAviation Civile, 7 Avenue Édouard Belin, CS 54005, Toulouse Cedex 4, 31055, France

  2. PADiff: Predictive and Adaptive Diffusion Policies for Ad Hoc Teamwork

    Nov 10, 2025Hohei Chan, Xinzhi Zhang, Antao Xiang +2Multi-Agent CoordinationMulti-Agent Collaboration

    School of Software Engineering, South China University of Technology, Guangzhou, China · Shanghai Jiao Tong University, Shanghai, China

  3. A Game-Theoretic Spatio-Temporal Reinforcement Learning Framework for Collaborative Public Resource Allocation

    Oct 30, 2025Songxin Lei, Qiongyan Wang, Yanchen Zhu +6Multi-Agent CoordinationReinforcement Learning

    The Hong Kong University of Science and Technology (Guangzhou) · Peking University · Beijing Institute of Technology +1

  4. 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

  5. MIMIC-D: Multi-modal Imitation for MultI-agent Coordination with Decentralized Diffusion Policies

    Sep 17, 2025Dayi Dong, Maulik Bhatt, Seoyeon Choi +1Multi-Agent CoordinationDiffusion Policy

    Department of Mechanical Engineering, University of California Berkeley, Berkeley, CA 94709, USA

  6. Self-Supervised Goal-Reaching Results in Multi-Agent Cooperation and Exploration

    Sep 12, 2025Chirayu Nimonkar, Shlok Shah, Catherine Ji +1Multi-Agent CoordinationRL Exploration

    Princeton University

  7. MAPF-World: Action World Model for Multi-Agent Path Finding

    Aug 16, 2025Zhanjiang Yang, Yueming Li, Yang Shen +2Multi-Agent Path FindingMulti-Agent Planning

    Shenzhen Technology University, China. · University of Technology Sydney, Australia.

  8. Hierarchical Message-Passing Policies for Multi-Agent Reinforcement Learning

    Jul 31, 2025Tommaso Marzi, Cesare Alippi, Andrea CiniMulti-Agent CoordinationHierarchical RL

    IDSIA USI-SUPSI, Università della Svizzera italiana, Lugano, Switzerland · Politecnico di Milano, Milan, Italy · EPFL, Lausanne, Switzerland

  9. United Minds or Isolated Agents? Exploring Coordination of LLMs under Cognitive Load Theory

    Jun 7, 2025HaoYang Shang, Xuan Liu, Zi Liang +3Multi-Agent CoordinationMulti-Agent Reasoning

    Hong Kong University of Science and Technology · University of California San Diego · Hong Kong Polytechnic University

  10. LOOP-MAC: Learning-Based Multi-Agent Coordination with Guaranteed Local Feasibility in a Virtual Power Plant

    Oct 27, 2023Meiyi Li, Lucas Ruda, Javad MohammadiMulti-Agent CoordinationPower Systems