Cooperation on the Fly: Exploring Language Agents for Ad Hoc Teamwork in the Avalon Game

Understand

Multi-agent collaboration with Large Language Models (LLMs) demonstrates proficiency in basic tasks, yet its efficiency in more complex scenarios remains unexplored.

• In gaming environments, these agents often face situations without established coordination protocols, requiring them to make intelligent inferences about teammates from limited data.
• This problem motivates the area of ad hoc teamwork, in which an agent may potentially cooperate with a variety of teammates to achieve a shared goal.
• Our study focuses on the ad hoc teamwork problem where the agent operates in an environment driven by natural language.