Defense and security planning under resource uncertainty and multi‐period commitments
Abstract
The public sector is characterized by hierarchical and interdependent organizations. For defense and security applications in particular, a higher authority is generally responsible for allocating resources among subordinate organizations. These subordinate organizations conduct long‐term planning based on both uncertain resources and an uncertain operating environment. This article develops a modeling framework and multiple solution methodologies for subordinate organizations to use under such conditions. We extend the adversarial risk analysis approach to a stochastic game via a decomposition into a Markov decision process. This allows the subordinate organization to encode its beliefs in a Bayesian manner such that long‐term policies can be built to maximize its expected utility. The modeling framework we develop is illustrated in a realistic counter‐terrorism use case, and the efficacy of our solutions are evaluated via comparisons to alternatively constructed policies.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Aug 08, 2022
- Source ID
- 10.1002/nav.22071
Entities
People
- David Banks
- Keru Wu
- William N. Caballero
Organizations
- Air Force Office of Scientific Research
- Duke University
- National Science Foundation of Sri Lanka
- United States Air Force Academy