Decision Aiding Through Bayesian Inference and Quasi-Axiomatic Theorem (Innovative Decision Aid)
Small Business Information
DANIEL H. WAGNER ASSOC., INC. (Currently Daniel H. Wagner, Associates, Incorporated)
40 Lloyd Avenue, Suite 200, Malvern, PA, 19355
Dr. Joseph H. Discenza
AbstractThis 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.
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