Command-and-Control System Analysis and Delineation of Possible Areas for Machine Learning

Authors

  • Petr Gallus Department of Informatics and Cyber Operations, Unviersity of Defence, Czech Republic
  • Petr Františ Department of Informatics and Cyber Operations, Unviersity of Defence, Czech Republic

DOI:

https://doi.org/10.3849/aimt.01948

Keywords:

Command-and-control, Artificial intelligence, Machine Learning, Military system, Simulation, Neural Network

Abstract

This paper explores AI and machine learning integration in military command-and-control (C2) systems, enhancing decision-making and operational efficiency. It examines AI applications across military levels, emphasizing predictive analytics, anomaly detection, and pattern recognition for improved situational awareness. Using the WASP simulation system, the study develops a neural network for scenario planning, highlighting simulators’ role in AI training. Results show AI’s potential to automate troop movement, command post deployment, and enemy maneuver recognition. The findings suggest AI-driven adaptability in dynamic battlefield environments. Future research will focus on advanced simulations and AI applications for military decision-making, reinforcing AI’s strategic role in modern warfare.a

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Published

03-10-2025

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Section

Case study

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How to Cite

Gallus, P., & Františ, P. (2025). Command-and-Control System Analysis and Delineation of Possible Areas for Machine Learning. Advances in Military Technology, 20(2), 389-407. https://doi.org/10.3849/aimt.01948

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