A Framework for Engineering Human/Agent Teaming Systems
Abstract
The increasing capabilities of autonomous systems offer the potential for more effective teaming with humans. Effective human/agent teaming is facilitated by a mutual understanding of the team objective and how that objective is decomposed into team roles. This paper presents a framework for engineering human/agent teams that delineates the key human/agent teaming components, using TDF-T diagrams to design the agents/teams and then present contextualised team cognition to the human team members at runtime. Our hypothesis is that this facilitates effective human/agent teaming by enhancing the human's understanding of their role in the team and their coordination requirements. To evaluate this hypothesis we conducted a study with human participants using our user interface for the StarCraft strategy game, which presents pertinent, instantiated TDF-T diagrams to the human at runtime. The performance of human participants in the study indicates that their ability to work in concert with the non-player characters in the game is significantly enhanced by the timely presentation of a diagrammatic representation of team cognition.
Cite
Text
Evertsz and Thangarajah. "A Framework for Engineering Human/Agent Teaming Systems." AAAI Conference on Artificial Intelligence, 2020. doi:10.1609/AAAI.V34I03.5629Markdown
[Evertsz and Thangarajah. "A Framework for Engineering Human/Agent Teaming Systems." AAAI Conference on Artificial Intelligence, 2020.](https://mlanthology.org/aaai/2020/evertsz2020aaai-framework/) doi:10.1609/AAAI.V34I03.5629BibTeX
@inproceedings{evertsz2020aaai-framework,
title = {{A Framework for Engineering Human/Agent Teaming Systems}},
author = {Evertsz, Rick and Thangarajah, John},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2020},
pages = {2477-2484},
doi = {10.1609/AAAI.V34I03.5629},
url = {https://mlanthology.org/aaai/2020/evertsz2020aaai-framework/}
}