Human-Machine Teaming for UAVs: An Experimentation Platform
Laila El Moujtahid, Sai Krishna Gottipati, Clod\'eric Mars and, Matthew E. Taylor

TL;DR
This paper introduces the Cogment platform, a lightweight experimentation environment designed to facilitate research and development of human-machine teaming in defense and critical systems involving heterogeneous AI agents and humans.
Contribution
The paper presents the Cogment platform, a novel experimentation tool enabling complex human-AI team interactions for research in defense environments.
Findings
Platform supports heterogeneous multi-agent systems
Used in academic research and defense scenarios
Facilitates development and validation of human-machine teaming algorithms
Abstract
Full automation is often not achievable or desirable in critical systems with high-stakes decisions. Instead, human-AI teams can achieve better results. To research, develop, evaluate, and validate algorithms suited for such teaming, lightweight experimentation platforms that enable interactions between humans and multiple AI agents are necessary. However, there are limited examples of such platforms for defense environments. To address this gap, we present the Cogment human-machine teaming experimentation platform, which implements human-machine teaming (HMT) use cases that features heterogeneous multi-agent systems and can involve learning AI agents, static AI agents, and humans. It is built on the Cogment platform and has been used for academic research, including work presented at the ALA workshop at AAMAS this year [1]. With this platform, we hope to facilitate further research on…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsHuman-Automation Interaction and Safety
