mlsanityData to 14 Oct 2026

Diverse Agents for Ad-Hoc Cooperation in Hanabi

arXiv 1907.03840 ↗First posted 8 Jul 2019cs.AI cs.NEcited by 17

Not on the map. Why?

Abstract (arXiv)

In complex scenarios where a model of other actors is necessary to predict and interpret their actions, it is often desirable that the model works well with a wide variety of previously unknown actors. Hanabi is a card game that brings the problem of modeling other players to the forefront, but there is no agreement on how to best generate a pool of agents to use as partners in ad-hoc cooperation evaluation. This paper proposes Quality Diversity algorithms as a promising class of algorithms to generate populations for this purpose and shows an initial implementation of an agent generator based on this idea. We also discuss what metrics can be used to compare such generators, and how the proposed generator could be leveraged to help build adaptive agents for the game.

Key facts. Cited by 17 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 Jul 2019.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 5; 2022: 4; 2023: 4; 2024: 2; 2025: 2.

17 papers.

Sort:

  1. 2021Generating and Blending Game Levels via Quality-Diversity in the Latent Space of a Variational Autoencodercited by 27
  2. 2022Any-Play: An Intrinsic Augmentation for Zero-Shot Coordinationcited by 23
  3. 2021Collaborative Visual Navigationcited by 18
  4. 2021Learned Belief Search: Efficiently Improving Policies in Partially Observable Settingscited by 10
  5. 2023Referential communication in heterogeneous communities of pre-trained visual deep networkscited by 10
  6. 2023Towards Few-shot Coordination: Revisiting Ad-hoc Teamplay Challenge In the Game of Hanabicited by 10
  7. 2022On-the-fly Strategy Adaptation for ad-hoc Agent Coordinationcited by 7
  8. 2021Generating Diverse and Competitive Play-Styles for Strategy Gamescited by 6
  9. 2022On the Impossibility of Learning to Cooperate with Adaptive Partner Strategies in Repeated Gamescited by 5
  10. 2024Measuring Diversity of Game Scenarioscited by 5
  11. 2023Mix-ME: Quality-Diversity for Multi-Agent Learningcited by 4
  12. 2022Is Vanilla Policy Gradient Overlooked? Analyzing Deep Reinforcement Learning for Hanabicited by 3
5 more
  1. 2025Improving Human-AI Coordination through Online Adversarial Training and Generative Modelscited by 3
  2. 2021Playing Against the Board: Rolling Horizon Evolutionary Algorithms Against Pandemiccited by 1
  3. 2023Behavioral Differences is the Key of Ad-hoc Team Cooperation in Multiplayer Games Hanabicited by 1
  4. 2024Adapting to Teammates in a Cooperative Language Gamecited by 1
  5. 2025Generalizable Agent Modeling for Agent Collaboration-Competition Adaptation with Multi-Retrieval and Dynamic Generationcited by 0