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

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.

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Publication Details

Journal
Proceedings of the AAAI Symposium Series
Published
2025-05-28
DOI
https://doi.org/10.1609/aaaiss.v5i1.35579
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Christopher MacLellan, Qiao Zhang
Proceedings of the AAAI Symposium Series
Human-Automation Interaction and Safety
article

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

Christopher MacLellan, Qiao Zhang
article en

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.

Proceedings of the AAAI Symposium SeriesVol. 5(1)
Georgia Institute of Technology (US)
Carnegie Mellon University, Strong, University of California, San Diego
Openalex Percentile: Top 87%
Human-Automation Interaction and Safety
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