Military operations demand responsible, safe, and robust feedback assessment mechanisms to ensure the proper coordination and cooperation between human agents and AI systems in various dynamic and uncertain conditions. Taking into account an existing gap in relation to research and practitioner studies and efforts dedicated to understanding, analysing, and modelling feedback in the context of military human-AI teaming, this research proposes a computational ontology for feedback representation and assessment in this context following the Design Science Research methodology in a Knowledge Representation and Reasoning approach using the complex systems theory. This represents an adaptive, interoperable, and scalable intelligent model that captures time, space, and force dimensions while accounting the roles, tasks, decisions, and mental models of the teammate agents for assuring trustable, responsible, and effective military decision-making, and strengthening the resilience and safety of human-AI teaming in various environments.
Maathuis, C & Cools, K 2025, FHATMO: Feedback Model for Human-AI Teaming in Military Operations. in P Kolar (ed.), 2025 International Conference on Military Technologies (ICMT) . International Conference on Military Technologies, IEEE, pp. 1-6, International Conference on Military Technologies 2025, 27/05/25. https://doi.org/10.1109/ICMT65201.2025.11061328
Maathuis, C., & Cools, K. (2025). FHATMO: Feedback Model for Human-AI Teaming in Military Operations. In P. Kolar (Ed.), 2025 International Conference on Military Technologies (ICMT) (pp. 1-6). (International Conference on Military Technologies). IEEE. https://doi.org/10.1109/ICMT65201.2025.11061328
@inproceedings{99f005b44afb47fb861651cfd5e6aa4c,
title = "FHATMO: Feedback Model for Human-AI Teaming in Military Operations",
abstract = "Military operations demand responsible, safe, and robust feedback assessment mechanisms to ensure the proper coordination and cooperation between human agents and AI systems in various dynamic and uncertain conditions. Taking into account an existing gap in relation to research and practitioner studies and efforts dedicated to understanding, analysing, and modelling feedback in the context of military human-AI teaming, this research proposes a computational ontology for feedback representation and assessment in this context following the Design Science Research methodology in a Knowledge Representation and Reasoning approach using the complex systems theory. This represents an adaptive, interoperable, and scalable intelligent model that captures time, space, and force dimensions while accounting the roles, tasks, decisions, and mental models of the teammate agents for assuring trustable, responsible, and effective military decision-making, and strengthening the resilience and safety of human-AI teaming in various environments.",
author = "Clara Maathuis and Kasper Cools",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; International Conference on Military Technologies 2025 ; Conference date: 27-05-2025 Through 31-05-2025",
year = "2025",
doi = "10.1109/ICMT65201.2025.11061328",
language = "English",
isbn = "9798331523398",
series = "International Conference on Military Technologies",
publisher = "IEEE",
pages = "1--6",
editor = "Petr Kolar",
booktitle = "2025 International Conference on Military Technologies (ICMT)",
url = "https://icmt2025.cz",
}