Air Dominance Through Machine Learning: A Preliminary Exploration of Artificial Intelligence–Assisted Mission Planning
Li Ang Zhang, Jia Xu, Dara Gold, Jeff Hagen, Ajay Kochhar, Andrew J. Lohn, Osonde Osoba
Abstract
U.S. air superiority is being challenged by competitors. The authors of this report demonstrate a prototype of a proof-of-concept artificial intelligence system to help develop and evaluate new concepts of operations for the air domain. The initial findings highlight both the potential of reinforcement learning to tackle complex, collaborative air mission planning problems, and some significant challenges facing this approach.
Topics & Concepts
Competitor analysisReinforcement learningDominance (genetics)Artificial intelligenceComputer scienceDomain (mathematical analysis)Air combatEngineeringOperations researchBusinessMathematicsGeneChemistryMarketingBiochemistryMathematical analysisMilitary Strategy and TechnologyMilitary Defense Systems AnalysisAir Traffic Management and Optimization