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Organizational and Cultural Criteria for Adversary Modeling (OCCAM)

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: F33615-03-M-6307
Agency Tracking Number: O022-0480
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Timeline
Solicitation Year: N/A
Award Year: 2002
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
625 Mount Auburn Street
Cambridge, MA 02138
United States
DUNS: 115243701
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Jonathan Pfautz
 Senior Scientist
 (617) 491-3474
 jpfautz@cra.com
Business Contact
 Paul Gonsalves
Title: Vice President
Phone: (617) 491-3474
Email: pgonsalves@cra.com
Research Institution
N/A
Abstract

"We propose a Phase I program to develop and demonstrate an analyst decision aid that incorporates Organizational and Cultural Criteria in Adversary Modeling (OCCAM). We define cultural criteria (i.e., behavior moderators) as influences upon individualdecision-making and behavior that arise from affiliations with specific groups; where `group' ranges from family through professional organizations to nation and religion. This uniform conceptualization of cultural behavior moderators lends itself tooperational definitions that enable effective computational behavior prediction. Four core components characterize our approach. First, we will identify key factors moderating behavior, from psychological theory and practical field knowledge. Second, wewill develop methods for augmenting sparse and uncertain data sets characterizing asymmetric operations by inferring these key factors from the individual's group affiliations. Third, we will develop a toolkit of knowledge-based methods for behaviorprediction, and evaluate the applicability of several of these in a suitable operational scenario. This toolkit will allow us to generate ranges of possible, plausible behaviors, reflecting the challenge of unequivocal behavior prediction. Fourth, wewill integrate these concepts and methods into a computerized decision-aid that explicitly represents the uncertainty inherent in the data, as well as the reliability of the prediction methods. We

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

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