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Proceedings Paper

Theoretical development of multi-domain command and control
Author(s): Jason Crane; Islam Hussein; Ronnie Mainieri; Lorraine Weis
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Paper Abstract

We are developing an agent-based model that allows us to explore control and distributed machine learning concepts in a systems-of-systems framework. The model captures the complex interactions between vehicles with very different operational tempos (such as satellites and unmanned aerial vehicles (UAVs)) and a variety of environmental elements (communication towers, objects of interest, etc.). Treating the model as a complex adaptive system, we can explore issues of controllability and observability, such as the constraints needed to maintain multi-vehicle formations under diverse conditions, and scaling questions, such as the data rates among vehicles and control centers under diverse system parameters.

Paper Details

Date Published: 10 May 2019
PDF: 8 pages
Proc. SPIE 11006, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, 1100605 (10 May 2019); doi: 10.1117/12.2518894
Show Author Affiliations
Jason Crane, L3 Applied Defense Solutions (United States)
Islam Hussein, L3 Applied Defense Solutions (United States)
Ronnie Mainieri, L3 Applied Defense Solutions (United States)
Lorraine Weis, L3 Applied Defense Solutions (United States)


Published in SPIE Proceedings Vol. 11006:
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications
Tien Pham, Editor(s)

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