Army Probabilistic Inference and Decision Engine (Army - PRIDE)

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911QY-09-C-0032
Agency Tracking Number: A083-186-0395
Amount: $119,998.00
Phase: Phase I
Program: SBIR
Awards Year: 2009
Solicitation Year: 2008
Solicitation Topic Code: A08-186
Solicitation Number: 2008.3
Small Business Information
1235 South Clark Street, Suite 400, Arlington, VA, 22202
DUNS: 036593457
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 David Lee
 Senior Engineer
 (703) 414-5087
Business Contact
 Kelly McClelland
Title: Director, Corporate Business Office
Phone: (703) 414-5024
Research Institution
The U.S. Army Natick Soldier Center (NSC) and Army Materiel Systems Analysis Activity (AMSAA) are leading an effort to develop a robust constructive force-on-force simulation that accurately represents individual Ground Soldiers (GS) and dismounted Small Combat Units (SCU). The purpose of the Infantry Warrior Simulation (IWARS) is to assess the impact and value of information on small unit operations, supporting the research, development and acquisition of warrior battlefield systems. Specifically, they intend the simulation to aid in understanding how information uncertainties, incomplete or missing information, conflicting information, and confidence in information sources impact GS decision-making processes and the equipment they use. The DECISIVE ANALYTICS Corporation (DAC) team will develop a powerful, probabilistic engine for decision-making under uncertainty. This generic engine will provide a stand-alone modeling capability that utilizes a robust mathematical framework, based on advanced real-time Bayesian network techniques, for modeling situational awareness and dynamic decision-making processes that are characterized by uncertain, incomplete or conflicting information. The engine will perform probabilistic modeling of GS decision processes for IWARS, or other constructive simulations. Additionally, the system will incorporate a Value of Information (VOI) component that improves the realism of the decision-making process, and provides an in-depth analysis capability.

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

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