Abstract:
Bayesian networks are useful for predicting future activities on the battlefield. Bayesian mathematics provides the most benefit in JDL fusion levels 2+, i.e. situation, ...Show MoreMetadata
Abstract:
Bayesian networks are useful for predicting future activities on the battlefield. Bayesian mathematics provides the most benefit in JDL fusion levels 2+, i.e. situation, threat, and performance assessment. However, these networks are exceedingly difficult for the average person to develop, much less a soldier in the middle of a war. We are in the process of developing a Bayesian modeling aid that walks the user through each step of the process, supplying help, suggesting alternatives, and translating their model into a human language description that is understandable by non-experts. This effort was originally funded as an AFRL Phase I SBIR (FA8750-06-C-0089) and is currently a Phase II SBIR. In this paper we will walk through the process of developing a Bayesian network and discuss how our tool helps at each step.
Published in: 2007 10th International Conference on Information Fusion
Date of Conference: 09-12 July 2007
Date Added to IEEE Xplore: 26 December 2007
CD:978-0-662-45804-3
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