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Albarado, K., Coduti, L., Aloisio, D., Robinson, S., Drown, D., & Javorsek, D. (2021). Alphamosaic: An artificially intelligent battle management architecture. Journal of Aerospace Information Systems, 1–11. 
Resource type: Journal Article
BibTeX citation key: Albarado2021
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Categories: Artificial Intelligence, Cognitive Science, Complexity Science, Computer Science, Data Sciences, Decision Theory, General, Military Science
Subcategories: Autonomous systems, Big data, Command and control, Decision making, Deep learning, Machine learning, Networked forces, Psychology of human-AI interaction
Creators: Albarado, Aloisio, Coduti, Drown, Javorsek, Robinson
Publisher:
Collection: Journal of Aerospace Information Systems
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Abstract
Warfare is increasing in complexity, speed, and scale—not only due to enhanced technological capabilities but also from the employment methodologies associated with them. Incorporating artificial intelligence (AI) technology into this realm is a cogent solution to help address these complications because of the reduced cost, reduced risk to human life, and increased capability to rapidly adapt to changing environments. However, the introduction of AI comes with a host of new considerations. If AI is to be successfully integrated into air combat, humans must be included in the AI processing loop, and human interaction with AI decision loops must be frictionless. Additionally, AI-supported battle management systems must be designed for high and increasing human trust across dynamically changing scenarios. This paper presents AlphaMosaic, an AI battle manager developed as part of the Defense Advanced Research Projects Agency Air Combat Evolution program that is designed to incorporate human feedback in a manner conducive to true manned–unmanned aircraft teaming in beyond visual range air-combat scenarios.
  
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