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Distributed Battle Management Techniques

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: N0017803C3105
Agency Tracking Number: 031-1490
Amount: $70,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Timeline
Solicitation Year: N/A
Award Year: 2003
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
1235 Jefferson Davis Highway, Suite 400
Arlington, VA 22202
United States
DUNS: 036593457
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Mark Frymire
 Senior Engineer
 (703) 414-5139
 mark.e.frymire@dac.us
Business Contact
 Kelly McClelland
Title: Manager, Business Ops
Phone: (703) 414-5023
Email: kelly.mcclelland@dac.us
Research Institution
N/A
Abstract

In the future Ballistic Missile Defense system, it will be necessary to coordinate the operations of many geographically dispersed system components to create an architecture with the best chance for defeating the threat. Though challenging, it is desiredthat this architecture be implemented in a distributed manner to avoid the need for a centralized controller to which all sensors transmit all of their information for processing and decision-making. In the research effort proposed here, the DecisiveAnalytics Corporation Team will implement a distributed C2BMC inference architecture using a framework called Multiply-Sectioned Bayesian Networks. Using this approach, which is based on recent advances in the artificial intelligence literature, it ispossible to decompose a unified Bayesian Network into subcomponents that operate at different locations, while exchanging data to maintain global consistency. Our implementation will employ the actual system models under development for Project Hercules,and we will assess computational performance with respect to various implementations of these cases.This background research will result in the development of a distributed multi-source fusion engine for inference. Potential application includes use in military command and control systems, and other decision support systems that involve time-criticaldecision-making under uncertainty, including crisis monitoring, and medical applications.

* Information listed above is at the time of submission. *

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