Authors: Paresh Chaudhary, Yancheng Liang, Daphne Chen, Simon S. Du, Natasha Jaques
Year: 2025
Published in: ArXiv
Institution: University of Washington
Research Area: Human-AI Coordination, Zero-Shot Coordination, Adversarial Training, Generative Models
Discipline: Artificial Intelligence, Human-Computer Interaction
The paper introduces GOAT, a novel framework combining pretrained generative models and adversarial training to improve human-AI coordination, achieving state-of-the-art performance on the Overcooked benchmark with real human partners.
Methods: The study utilized a frozen pretrained generative model to simulate cooperative agent policies and applied adversarial training to dynamically generate challenging human-AI interaction scenarios for training.
Key Findings: The effectiveness of GOAT in generalizing human-AI coordination strategies and its performance on the Overcooked benchmark.
