NT/SScct/m inheriumce, and modularization are supported. Thus far, LORE lacked a built-in model for inexact reasoning, which made it less suited to applications in which uncertainty plays a major role. For this reason, an existing model for the representation and propagation of uncertainty (Buchanan and Shortliffe's certainty facing model) was modified to make it applicable in a more general environment. Focusing Based on the Structure o f u ModelBased Dingaosb Nonteboom, P.; Leemeijex, G. B. Technische Univ. Twente, Euschede (Netherlands). Knowledge-Based Systems Group. Corp. S o m ~ Codes: 090700012; U1294434 Sponsor: National Aeronautics and Space Administration, Washington, DC. Report No.: MEMO-INF-91-41; UT-KBS-91-22 May 91 32p Iamguages: English
Journal Announcement: GRAI9208; STAR3005 Sponsored by Stlchting Knowledge Based Systems. HI'IS Prices: PC A03/MF A01 Country of Publication: Netherlands The high computational complexity of existing methods for model-based diagnom imposes a limit on the application of those methods in practical situations. Therefore, a lot of research is spent on methods that improve the tractability of model-based diagnosis. A new method for improving the tractability of modelbased diagnosis is presented. The ~ i n g mechanism used is restricted to a mbrA of the components in the model called the focus. This focus is selected during diagnosis, based on the structure of the model and the observed values at the system outputs and measurable connections in the model. Experiments have shown that focusing improves the practical applicability of modelbased dia~osis. A method for ordering the resulting set of diagnoses in a way analogous to determining a focus that is based on the structure of the model and observations available is discussed.