Automating Model Acquisition by Fault Knowledge Re-use, DR, the Diagnostic Remodeler Algorithm

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TypeArticle
ConferenceInternational Workshop on the Principles of Diagnosis, October 17-19, 1994., New Paltz, New York, USA
AbstractThis paper addresses the problem of automated model acquisition through there-use of fault knowledge. The Diagnostic Remodeler (DR) algorithm has been implemented for the automated generation of behavioural component models with an explicit representation of function by re-using fault-based knowledge. DR re-uses as its first application the fault-based knowledge of the Jet Engine Troubleshooting Assistant (JETA). DR extracts a model of the Main Fuel System using real-world engine fault knowledge and two types of background knowledge as input: device dependent and device independent background knowledge. To demonstrate DR's generality, it has also been applied to a coffee maker fault knowledge base to extract the component models of a full coffee device.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number38315
NPARC number8913934
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Record identifierf616d170-520b-4765-8023-10c71c9b5578
Record created2009-04-22
Record modified2016-05-09
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