Optimal Real time Decision Making in an Uncertain World
Abstract
Assessing the minimal amount of information-data needed to obtain provably optimal policies in making real time decisions under uncertainty is an open question. The objective of this research is to determine this information-data boundary and project it onto real world problems. To achieve this objective, this research will explore provably optimal policies for Generalized Sequential Stochastic Assignment Problems (GSSAPs). The models to be considered in this proposal are motivated by problems associated with the optimal allocation and utilization of military assets. Such problems move beyond the standard model assumptions, creating an opportunity for alternative approaches to describe computationally tractable optimal policies for such models.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 14, 2022
- Source ID
- FA95501910106
Entities
People
- Sheldon H. Jacobson
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Illinois Urbana–Champaign