Improving ORM utilizing Implicit Collaboration & Context Sensitive Fusion
Abstract
George Mason University has developed a scalable, information-based, real-time methodology for sensor management. We propose to continue the development of this research by extending it to include mission management. The objective of the proposed research is to extend our concept of goal lattices to implicit collaboration (IC) of intelligence gathering platforms. The expected result is that implicit collaboration will be shown to be an effective method of indirect control of intelligence collection assets. The public purpose of this research is to enable effective information gathering resource allocation in the event of an unplanned disaster. Our method of Orchestrated Resource Management includes: •Cognitive collection based on entropy changes in a probabilistic model of the situation represented in a SIEV-Net. •Intelligence valuation through the use of our method of goal lattices. Goal lattices provide a quantitative method of assigning mission goal values to both situation and measurement information. • Decision space search methods are implemented in our method of ordering situation information requests and sensor actions. • Plan-optimization processes are implemented in an Information Instantiator which orders the set of currently available sensor functions to determine an admissible set as well as evaluate them based on their expected information value rate.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 08, 2016
- Source ID
- N002441510047
Entities
People
- Kenneth Hintz
Organizations
- George Mason University
- United States Navy