Data-Adaptable Modeling and Optimization for Runtime Adaptable Systems
Abstract
The proposal is aimed to develop novel methods and approaches to support DDDAS runtime environments such as model-integrated approaches to holistic optimization of complex, dynamic, heterogeneous systems, addressing issues such as large optimization and configuration spaces, too large to statically optimize such systems, and the system composition itself is dynamic, with vehicles or sensors temporarily being made available, or performing tasks for which they may not have otherwise been intended.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 23, 2016
- Source ID
- FA95501510143
Entities
People
- Roman Lysecky
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Arizona