Ad Hoc Coordination
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Overview
Tagline Brand's website · 2026-10-04
Introduces robust, cheap, and reproducible 'human proxy agents' for evaluating human-AI coordination in complex games like Hanabi, addressing the limitations of traditional human evaluations, and provides a deliberately limited dataset to encourage data-efficient AI development.
Description Brand's website · 2026-10-04
The Ad-Hoc Human-AI Coordination Challenge (AH2AC2) is a research initiative and testbed designed to foster seamless coordination between AI agents and humans. It addresses the challenges of costly and difficult-to-reproduce human evaluations by introducing human proxy agents trained on a large-scale human dataset, making Hanabi an ideal environment for this research. The project open-sources a dataset and code, and presents baseline results for multi-player Hanabi scenarios.
Offerings
Core capabilities Brand's website · 2026-10-04
- The 'Ad-Hoc Human-AI Coordination Challenge' methodology
- human proxy agents
- and an open-source dataset of Hanabi games for human-AI coordination research.
Pricing Brand's website · 2026-10-04
Free and open-source for the code and dataset, academic paper publicly available via arXiv.
Audience
Target industry Brand's website · 2026-10-04
AI researchers, multiagent systems researchers, human-computer interaction researchers, and developers working on collaborative AI.
Landscape
Competitors Brand's website · 2026-10-04
- OpenAI Gym
- DeepMind Lab
- NeurIPS/ICLR/AAAI/IJCAI Shared Tasks/Competitions
- Hanabi Learning Environment (HLE)
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