✦ LIBER ✦

An algorithmic approach to combining belief functions

✍ Scribed by Bruce E. Tonn

Publisher: John Wiley and Sons
Year: 1998
Tongue: English
Weight: 913 KB
Volume: 11
Category: Article
ISSN: 0884-8173
DOI: 10.1002/(sici)1098-111x(199607)11:7<463::aid-int3>3.0.co;2-k

No coin nor oath required. For personal study only.

✦ Synopsis

Methods of combination are used to synthesize pieces of evidence of equal standing that represent different aspects of a specific system about which a diagnosis is to be made. Combination is distinct from consensus, when complete diagnoses rendered by different knowledge sources require synthesis, and conditionalization, where pieces of evidence to be synthesized have dissymmetric relationships to each other. The Dempster-Shafer Rule is the quintessential combination method. However, it has been criticized for its inability to handle inconsistent pieces of evidence and for the way it focuses the weight of evidence. This article presents an alternative combination method that is capable of handling inconsistent evidence and relates evidence focusing to the amount of information resident in pieces of evidence. The method is capable of combining belief functions. Future research should address extending the method to the combination of a broad class of imprecise probability functions.

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