Think and Play: Designing and Evaluating Human-AI Teaming Dynamics in Gaming Environments

Abstract

To investigate Human-Machine Teaming (HMT) dynamics---and how AI capabilities influence team behavior and performance---we propose a series of three studies to explore communication, coordination, and adaptation in HMT paradigms. To support these investigations, we are developing multiple AI agents and using collaborative games as testing environments to evaluate the human-AI team performance. This work contributes to two central topics in HMT research: 1) the bidirectional adjustments that human and AI agents may develop when working as a team and, 2) how different types of AI agents and interventions can impact the teaming efficiency in human-AI teaming.