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Proceedings Paper

Sensitivity analysis in probabilistic argumentation systems
Author(s): Yang Chen; Deepak Khosla
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Paper Abstract

Sensitivity analysis in an uncertainty reasoning system helps establish the relationship between the system output and the system parameters under a given input condition. Much work has been done in Bayesian reasoning and, in particular, Bayesian networks in the last decade. However, little work has been done in other uncertainty reasoning frameworks. In this paper, we introduce a sensitivity analysis method that is built upon the Probabilistic Argument System (PAS) framework. With the help of a PAS, we developed both approximate and closed-form formulas for sensitivity analysis that achieve the same functionalities as those developed for Bayesian networks recently reported in the literature. However, our approach can be applied for non-Bayesian reasoning as well as Bayesian reasoning, as Bayesian reasoning can be considered as a special case in PAS. For example, Demspter-Shafer (D-S) theory has a close tie with PAS. Therefore the approach described in this paper can be used to develop D-S reasoning systems. We give examples using an incomplete probabilistic model in PAS to illustrate the methods described in this paper.

Paper Details

Date Published: 28 March 2005
PDF: 11 pages
Proc. SPIE 5813, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2005, (28 March 2005); doi: 10.1117/12.603017
Show Author Affiliations
Yang Chen, HRL Labs., LLC (United States)
Deepak Khosla, HRL Labs., LLC (United States)


Published in SPIE Proceedings Vol. 5813:
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2005
Belur V. Dasarathy, Editor(s)

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