Acquiring Probabilistic Knowledge for Information Fusion

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8750-07-C-0055
Agency Tracking Number: F061-065-0901
Amount: $1,741,680.00
Phase: Phase II
Program: SBIR
Awards Year: 2007
Solicitation Year: 2006
Solicitation Topic Code: AF06-065
Solicitation Number: 2006.1
Small Business Information
DECISIVE ANALYTICS CORP.
1235 South Clark Street, Suite 400, Arlington, VA, 22202
DUNS: 036593457
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Jessica Bradley
 Manager, Intelligent Agen
 (703) 682-1735
 jessica.bradley@dac.us
Business Contact
 Kelly McClelland
Title: Director, Corporate Busin
Phone: (703) 414-5024
Email: kelly.mcclelland@dac.us
Research Institution
N/A
Abstract
Acquiring probabilistic knowledge for the development of fusion models can prove to be a difficult task. In many applications, the lack of availability of historical data forces the modelers to rely extensively on expert judgment techniques which traditionally requires a large amount of manpower and is exceedingly time-consuming. Under Phase I of this effort, the DAC Team has proven the feasibility of the Semi-Automated Building and Evaluation of Relational Models (SABER) technique. SABER provides an intuitive means for the non-expert to construct probabilistic models, quantitatively evaluate them, and identify “hotspots” in the network that are highly influential. In Phase II we plan to build on our Phase I prototype and implement and test the approach in operational environments. Through our partnerships with the Air Force Special Operations Command (AFSOC) and the Army’s 9th Infantry Regiment, we have operational users that will be aligned with our design-implement-test spiral development process. The end of Phase II will result in prototype software that has been battletested in Warfighting environments and is ready for Phase III transition.

* information listed above is at the time of submission.

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