Published:
2020-06-02
Proceedings:
Proceedings of the AAAI Conference on Artificial Intelligence, 34
Volume
Issue:
Vol. 34 No. 03: AAAI-20 Technical Tracks 3
Track:
AAAI Technical Track: Human-AI Collaboration
Downloads:
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.
DOI:
10.1609/aaai.v34i03.5629
AAAI
Vol. 34 No. 03: AAAI-20 Technical Tracks 3
ISSN 2374-3468 (Online) ISSN 2159-5399 (Print) ISBN 978-1-57735-835-0 (10 issue set)
Published by AAAI Press, Palo Alto, California USA Copyright © 2020, Association for the Advancement of Artificial Intelligence All Rights Reserved