Decision Aiding Through Bayesian Inference and Quasi-Axiomatic Theorem (Innovative Decision Aid)

Award Information
Agency:
Department of Defense
Branch
Army
Amount:
$99,947.00
Award Year:
1998
Program:
SBIR
Phase:
Phase I
Contract:
n/a
Award Id:
41480
Agency Tracking Number:
41480
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
DANIEL H. WAGNER ASSOC., INC. (Currently Daniel H. Wagner, Associates, Incorporated)
40 Lloyd Avenue, Suite 200, Malvern, PA, 19355
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Dr. Joseph H. Discenza
(757) 727-7700
Business Contact:
() -
Research Institution:
n/a
Abstract
This proposed research draws on classical Bayesian Inference combined with powerful new tools called Quasi-Axiomatic Theorem (QAT) to provide a comprehensive and adaptive situation analysis decision aid. The Bayesian Inference component provides automatic assessment of hypotheses based on the continuous arrival of positive (contact) and negative (search) information. The QAT component provides the adaptive mechanism by which new hypotheses can be formed in the presence of conflicting or seemingly erroneous data. A graphical user interface allows the operator to interact with the adaptive algorithms to create and assess hypotheses. BENEFITS: An adaptive system of algorithms promises to improve situation assessment and reduce confusion in the demanding, time~ritical environment of.the battlefield. These results can also be applied to police surveillance, counternarcotics and industrial intelligence analysis.

* information listed above is at the time of submission.

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