Air Dominance Through Machine Learning: A Preliminary Exploration of Artificial Intelligence-Assisted Mission Planning

By Dara Gold, Jia Xu, Li Ang Zhang

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.

• Format: Paperback
• Language: English
• ISBN: 1977405150
• ISBN13: 9781977405159
• Release Date: August 2020
• Publisher: RAND Corporation
• Length: 70 Pages
• Weight: 0.41 lbs.
• Dimensions: 0.1" x 8.5" x 11.0"