Date of Award
Master of Science
Department of Operational Sciences
Matthew J. Robbins, PhD
Military air battle managers face many challenges when directing operations in quickly evolving combat scenarios. These scenarios require rapid decisions to engage moving and unpredictable targets. In defensive operations, the success of a sequence of air battle management decisions is reflected by the friendly force's ability to maintain air superiority by defending friendly assets. We develop a Markov decision process (MDP) model of the air battle management (ABM)problem, wherein a set of unmanned combat aerial vehicles (UCAV) is tasked to defend a central asset from cruise missiles that arrive stochastically over time.
DTIC Accession Number
Liles, Joseph M. IV, "Improving Air Battle Management Target Assignment Processes via Approximate Dynamic Programming" (2021). Theses and Dissertations. 4930.