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Adaptive uncertainty management for a class of diagnostic expert systems

Published online by Cambridge University Press:  27 February 2009

Nikola Bogunović and
Tomislav Mesić
Nikola Bogunović
Affiliation:
Rudjer Bošković Institute, Zagreb, Croatia
Tomislav Mesić
Affiliation:
Rudjer Bošković Institute, Zagreb, Croatia
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Abstract

This paper gives a theoretical foundation and implementation details of data and control structures in a diagnostic expert system with adaptive uncertainty management. The considered problem covers a class of expert systems and the application domain in which the operating personnel actively monitor and control the outcome of an industrial manufacturing process. Based on subjective ranking of the latent fault in the final output product, the operator queries the expert system for a recommended corrective action. Subsequent successful or unsuccessful corrective actions consistently modify confidence measures of all corrective recommendations from the same fault set, according to the embedded analytical model. The described approach is based on the relational data representation and procedural control structures, as opposed to a more traditional declarative, production-based system.

Keywords

Expert SystemsProcess DiagnosisUncertainty Management

Information

Type
Articles
Information
AI EDAM , Volume 10 , Issue 5 , November 1996, pp. 421 - 429
Copyright
Copyright © Cambridge University Press 1996

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References

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