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Proceedings Paper

Representations of probablistic situations
Author(s): Jared Culbertson; Kirk Sturtz; Mark E. Oxley
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Paper Abstract

Determining a decision from data is an important DoD research area with far-reaching applications. In particular, the long-elusive goal of autonomous machines discovering the relations between entities within a situation has proved to be extremely dicult. Many current sensing systems are devoted to fusing information from a variety of heterogeneous sensors in order to characterize the entities and relationships in the data. This leads to the need for representations of relationships and situations which can model the uncertainty that is present in any system. We develop mathematics for representing a situation where the relations are uncertain and use the work of Meng to show how to compare probabilistic relations and situations.

Paper Details

Date Published: 17 May 2012
PDF: 11 pages
Proc. SPIE 8392, Signal Processing, Sensor Fusion, and Target Recognition XXI, 839212 (17 May 2012); doi: 10.1117/12.919861
Show Author Affiliations
Jared Culbertson, Air Force Research Lab. (United States)
Kirk Sturtz, Universal Mathematics (United States)
Mark E. Oxley, Air Force Institute of Technology (United States)

Published in SPIE Proceedings Vol. 8392:
Signal Processing, Sensor Fusion, and Target Recognition XXI
Ivan Kadar, Editor(s)

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