Representations of probablistic situations

Jared Culbertson; Kirk Sturtz; Mark E. Oxley

doi:10.1117/12.919861

17 May 2012 Representations of probablistic situations

Jared Culbertson, Kirk Sturtz, Mark E. Oxley

Proceedings Volume 8392, Signal Processing, Sensor Fusion, and Target Recognition XXI; 839212 (2012) https://doi.org/10.1117/12.919861
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

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.

Citation Download Citation

Jared Culbertson, Kirk Sturtz, and Mark E. Oxley "Representations of probablistic situations", Proc. SPIE 8392, Signal Processing, Sensor Fusion, and Target Recognition XXI, 839212 (17 May 2012); https://doi.org/10.1117/12.919861

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