mlsanityData to 7 Oct 2026

Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning

arXiv 2006.10412 ↗First posted 18 Jun 2020cs.LG cs.MA stat.MLcited by 37

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Abstract (arXiv)

Ad hoc teamwork is the challenging problem of designing an autonomous agent which can adapt quickly to collaborate with teammates without prior coordination mechanisms, including joint training. Prior work in this area has focused on closed teams in which the number of agents is fixed. In this work, we consider open teams by allowing agents with different fixed policies to enter and leave the environment without prior notification. Our solution builds on graph neural networks to learn agent models and joint-action value models under varying team compositions. We contribute a novel action-value computation that integrates the agent model and joint-action value model to produce action-value estimates. We empirically demonstrate that our approach successfully models the effects other agents have on the learner, leading to policies that robustly adapt to dynamic team compositions and significantly outperform several alternative methods.

Key facts. Cited by 37 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Jun 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 11; 2023: 7; 2024: 5; 2025: 11; 2026: 2.

37 papers.

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  1. 2022A Survey of Ad Hoc Teamwork Researchcited by 41
  2. 2023A Review of Cooperation in Multi-agent Learningcited by 27
  3. 2023Cooperation on the Fly: Exploring Language Agents for Ad Hoc Teamwork in the Avalon Gamecited by 27
  4. 2022Contrastive Identity-Aware Learning for Multi-Agent Value Decompositioncited by 19
  5. 2022Generating Teammates for Training Robust Ad Hoc Teamwork Agents via Best-Response Diversitycited by 17
  6. 2024N-Agent Ad Hoc Teamworkcited by 15
  7. 2023Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agentscited by 13
  8. 2022A General Learning Framework for Open Ad Hoc Teamwork Using Graph-based Policy Learningcited by 12
  9. 2023Tackling Cooperative Incompatibility for Zero-Shot Human-AI Coordinationcited by 12
  10. 2021On the Use and Misuse of Absorbing States in Multi-agent Reinforcement Learningcited by 10
  11. 2024Fast Peer Adaptation with Context-aware Explorationcited by 7
  12. 2024Open Ad Hoc Teamwork with Cooperative Game Theorycited by 6
25 more
  1. 2025ROTATE: Regret-driven Open-ended Training for Ad Hoc Teamworkcited by 6
  2. 2022Learning Task Embeddings for Teamwork Adaptation in Multi-Agent Reinforcement Learningcited by 5
  3. 2024Assessing the Impact of Distribution Shift on Reinforcement Learning Performancecited by 4
  4. 2025Communication-Efficient Desire Alignment for Embodied Agent-Human Adaptationcited by 4
  5. 2025Shapley Machine: A Game-Theoretic Framework for N-Agent Ad Hoc Teamworkcited by 4
  6. 2022Deep Reinforcement Learning for Multi-Agent Interactioncited by 3
  7. 2024Inverse Attention Agents for Multi-Agent Systemscited by 3
  8. 2022Review of Metrics to Measure the Stability, Robustness and Resilience of Reinforcement Learningcited by 2
  9. 2023Knowledge-based Reasoning and Learning under Partial Observability in Ad Hoc Teamworkcited by 2
  10. 2025Unsupervised Partner Design Enables Robust Ad-hoc Teamworkcited by 2
  11. 2025Challenges in Credit Assignment for Multi-Agent Reinforcement Learning in Open Agent Systemscited by 2
  12. 2026Shaping Zero-Shot Coordination via State Blockingcited by 2
  13. 2022Ad Hoc Teamwork in the Presence of Adversariescited by 1
  14. 2023Goals are Enough: Inducing AdHoc cooperation among unseen Multi-Agent systems in IMFscited by 1
  15. 2025Zero-Shot Coordination in Ad Hoc Teams with Generalized Policy Improvement and Difference Rewardscited by 1
  16. 2022RACA: Relation-Aware Credit Assignment for Ad-Hoc Cooperation in Multi-Agent Deep Reinforcement Learningcited by 0
  17. 2022Knowledge-based and Data-driven Reasoning and Learning for Ad Hoc Teamworkcited by 0
  18. 2022Classifying Ambiguous Identities in Hidden-Role Stochastic Games with Multi-Agent Reinforcement Learningcited by 0
  19. 2023Latent Interactive A2C for Improved RL in Open Many-Agent Systemscited by 0
  20. 2025AT-Drone: Benchmarking Adaptive Teaming in Multi-Drone Pursuitcited by 0
  21. 2025Generic-to-Specific Reasoning and Learning for Scalable Ad Hoc Teamworkcited by 0
  22. 2025PACT: Phenotype-Aware Contrastive Team Representation for Multi-Phenotype Grouped Ad Hoc Teamworkcited by 0
  23. 2025PADiff: Predictive and Adaptive Diffusion Policies for Ad Hoc Teamworkcited by 0
  24. 2025Graph Neural Networks, Deep Reinforcement Learning and Probabilistic Topic Modeling for Strategic Multiagent Settingscited by 0
  25. 2026PLATO: Pointer Learner for Agent and Task Opennesscited by 0