mlsanityData to 14 Oct 2026

Learning Bilateral Team Formation in Cooperative Multi-Agent Reinforcement Learning

arXiv 2506.20039 ↗First posted 24 Jun 2025cs.MA cs.AI cs.GTcited by 0

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Abstract (arXiv)

Team formation and the dynamics of team-based learning have drawn significant interest in the context of Multi-Agent Reinforcement Learning (MARL). However, existing studies primarily focus on unilateral groupings, predefined teams, or fixed-population settings, leaving the effects of algorithmic bilateral grouping choices in dynamic populations underexplored. To address this gap, we introduce a framework for learning two-sided team formation in dynamic multi-agent systems. Through this study, we gain insight into what algorithmic properties in bilateral team formation influence policy performance and generalization. We validate our approach using widely adopted multi-agent scenarios, demonstrating competitive performance and improved generalization in most scenarios.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 16 of its 34 references that are in the map. First posted on arXiv 24 Jun 2025.

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References · 16

  1. 2016HyperNetworkscited by 1,027
  2. 2021The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Gamescited by 942
  3. 2018QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learningcited by 708
  4. 2019The StarCraft Multi-Agent Challengecited by 597
  5. 2017Value-Decomposition Networks For Cooperative Multi-Agent Learningcited by 503
  6. 2020RODE: Learning Roles to Decompose Multi-Agent Taskscited by 125
  7. 2019Competing Bandits in Matching Marketscited by 56
  8. 2020Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learningcited by 38
  9. 2018Multi-Agent Common Knowledge Reinforcement Learningcited by 31
  10. 2021Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Compositioncited by 30
  11. 2022Scalable Multi-Agent Reinforcement Learning for Warehouse Logistics with Robotic and Human Co-Workerscited by 30
  12. 2020Multi-Agent Collaboration via Reward Attribution Decompositioncited by 17
4 more
  1. 2024Improved Bandits in Many-to-one Matching Markets with Incentive Compatibilitycited by 7
  2. 2024Putting Gale & Shapley to Work: Guaranteeing Stability Through Learningcited by 7
  3. 2016Stable Matching with Uncertain Linear Preferencescited by 6
  4. 2024Field Deployment of Multi-Agent Reinforcement Learning Based Variable Speed Limit Controllerscited by 2

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  1. 2024Fully Decentralized Cooperative Multi-Agent Reinforcement Learning: A Survey
  2. 2025An Extended Benchmarking of Multi-Agent Reinforcement Learning Algorithms in Complex Fully Cooperative Tasks
  3. 2025Hierarchical Reinforcement Learning for Optimal Agent Grouping in Cooperative Systems
  4. 2024Game Theory and Multi-Agent Reinforcement Learning : From Nash Equilibria to Evolutionary Dynamics
  5. 2025Structured Cooperative Multi-Agent Reinforcement Learning: a Bayesian Network Perspective
  6. 2025IPPO Learns the Game, Not the Team: A Study on Generalization in Heterogeneous Agent Teams
  7. 2024Scaling Team Coordination on Graphs with Reinforcement Learning
  8. 2025LLM Collaboration With Multi-Agent Reinforcement Learning