Date of Award

3-2021

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Operational Sciences

First Advisor

Matthew J. Robbins, PhD

Abstract

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.

AFIT Designator

AFIT-ENS-MS-21-M-173

DTIC Accession Number

AD1131215

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