mlsanityData to 7 Oct 2026

The Hanabi Challenge: A New Frontier for AI Research

arXiv 1902.00506 ↗First posted 1 Feb 2019cs.LG cs.AI stat.MLcited by 194

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Cited by 21 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

From the early days of computing, games have been important testbeds for studying how well machines can do sophisticated decision making. In recent years, machine learning has made dramatic advances with artificial agents reaching superhuman performance in challenge domains like Go, Atari, and some variants of poker. As with their predecessors of chess, checkers, and backgammon, these game domains have driven research by providing sophisticated yet well-defined challenges for artificial intelligence practitioners. We continue this tradition by proposing the game of Hanabi as a new challenge domain with novel problems that arise from its combination of purely cooperative gameplay with two to five players and imperfect information. In particular, we argue that Hanabi elevates reasoning about the beliefs and intentions of other agents to the foreground. We believe developing novel techniques for such theory of mind reasoning will not only be crucial for success in Hanabi, but also in broader collaborative efforts, especially those with human partners. To facilitate future research, we introduce the open-source Hanabi Learning Environment, propose an experimental framework for the research community to evaluate algorithmic advances, and assess the performance of current state-of-the-art techniques.

Key facts. Cited by 194 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Feb 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 24; 2022: 27; 2023: 39; 2024: 37; 2025: 37; 2026: 30.

194 papers.

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  1. 2023CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Societycited by 1,348
  2. 2021The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Gamescited by 903
  3. 2023Building Cooperative Embodied Agents Modularly with Large Language Modelscited by 231
  4. 2022Compute Trends Across Three Eras of Machine Learningcited by 161
  5. 2024BALROG: Benchmarking Agentic LLM and VLM Reasoning On Gamescited by 141
  6. 2021Collaborating with Humans without Human Datacited by 139
  7. 2022SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learningcited by 118
  8. 2024Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learningcited by 80
  9. 2021Off-Belief Learningcited by 72
  10. 2024Simplifying Deep Temporal Difference Learningcited by 71
  11. 2023LLM-Coordination: Evaluating and Analyzing Multi-agent Coordination Abilities in Large Language Modelscited by 65
  12. 2023Strategic Reasoning with Language Modelscited by 64
38 more
  1. 2023Language Instructed Reinforcement Learning for Human-AI Coordinationcited by 61
  2. 2023JaxMARL: Multi-Agent RL Environments and Algorithms in JAXcited by 59
  3. 2021ToM2C: Target-oriented Multi-agent Communication and Cooperation with Theory of Mindcited by 57
  4. 2022Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real worldcited by 56
  5. 2021Modeling Strong and Human-Like Gameplay with KL-Regularized Searchcited by 50
  6. 2024COMBO: Compositional World Models for Embodied Multi-Agent Cooperationcited by 47
  7. 2023Welfare Diplomacy: Benchmarking Language Model Cooperationcited by 43
  8. 2022A Survey of Ad Hoc Teamwork Researchcited by 41
  9. 2021Evaluation of Human-AI Teams for Learned and Rule-Based Agents in Hanabicited by 37
  10. 2021Continuous Coordination As a Realistic Scenario for Lifelong Learningcited by 31
  11. 2022K-level Reasoning for Zero-Shot Coordination in Hanabicited by 30
  12. 2023Cooperative Open-ended Learning Framework for Zero-shot Coordinationcited by 30
  13. 2024Position: Theory of Mind Benchmarks are Broken for Large Language Modelscited by 30
  14. 2023Decision-Oriented Dialogue for Human-AI Collaborationcited by 29
  15. 2023A Review of Cooperation in Multi-agent Learningcited by 27
  16. 2021On the Critical Role of Conventions in Adaptive Human-AI Collaborationcited by 26
  17. 2021Variational Automatic Curriculum Learning for Sparse-Reward Cooperative Multi-Agent Problemscited by 25
  18. 2021Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systemscited by 24
  19. 2025SPIN-Bench: How Well Do LLMs Plan Strategically and Reason Socially?cited by 24
  20. 2022Continuously Discovering Novel Strategies via Reward-Switching Policy Optimizationcited by 23
  21. 2023NOPA: Neurally-guided Online Probabilistic Assistance for Building Socially Intelligent Home Assistantscited by 23
  22. 2021Student of Games: A unified learning algorithm for both perfect and imperfect information gamescited by 22
  23. 2022Any-Play: An Intrinsic Augmentation for Zero-Shot Coordinationcited by 22
  24. 2022Mind the gap: Challenges of deep learning approaches to Theory of Mindcited by 21
  25. 2022MARLlib: A Scalable and Efficient Multi-agent Reinforcement Learning Librarycited by 21
  26. 2021Neural Recursive Belief States in Multi-Agent Reinforcement Learningcited by 18
  27. 2021Scalable Online Planning via Reinforcement Learning Fine-Tuningcited by 18
  28. 2021Emergent Communication under Competitioncited by 17
  29. 2022Model-based Multi-agent Reinforcement Learning: Recent Progress and Prospectscited by 17
  30. 2024Human-compatible driving partners through data-regularized self-play reinforcement learningcited by 17
  31. 2022Policy Optimization for Markov Games: Unified Framework and Faster Convergencecited by 16
  32. 2022Equivariant Networks for Zero-Shot Coordinationcited by 16
  33. 2024A Survey of Imitation Learning Methods, Environments and Metricscited by 16
  34. 2025A Survey of Continual Reinforcement Learningcited by 16
  35. 2023Computational Language Acquisition with Theory of Mindcited by 15
  36. 2024The RL/LLM Taxonomy Tree: Reviewing Synergies Between Reinforcement Learning and Large Language Modelscited by 15
  37. 2022Coordination with Humans via Strategy Matchingcited by 14
  38. 2023Games for Artificial Intelligence Research: A Review and Perspectivescited by 14

50 most cited of 194 All 194 (JSON)