Hierarchical High Level Information Fusion (H2LIFT)
Abstract
The primary objective of this effort was the progression of Level 2/3 fusion of informational content to obtain an advanced multi-intelligent system for hierarchical high-level decision making processes. The goal was to develop an information integration mechanism to simplify human decision making solving operational problems. As technology continues to advance and the proliferation of sensors in all platform increases, human decision makers are being overwhelmed with data. In this research, the CUBRC proposed a cost effective two-year program of a novel approach in the near "real-time" ranking/formulation of hypotheses in asymmetric warfare scenarios. In particular, CUBRC introduced the Hierarchical High Level Information Fusion Technologies (H2LIFT) architecture with the following objectives: develop H2LIFT Architecture and algorithms for GWOT/MDA threats; develop prototype software that implements H2LIFT architecture and algorithms; and develop a simulation based tool for performance evaluation and analysis.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 15, 2008
- Accession Number
- ADA486330
Entities
People
- Adam Stotz
- Aggamemnon Crassidis
- John Crassidis
- Moises Sudit
- Rakesh Nagi
- Tracy Vongonten
Organizations
- Calspan-University of Buffalo Research Center