The use of design descriptions in automated diagnosis
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Modeling digital circuits for troubleshooting
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Hierarchical model-based diagnosis
Readings in model-based diagnosis
What's in SD?: Towards a theory of modeling for diagnosis
Readings in model-based diagnosis
Characterizing diagnoses and systems
Artificial Intelligence
Hierarchical model-based diagnosis based on structural abstraction
Artificial Intelligence
Automatic abstraction in component-based diagnosis driven by system observability
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
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We propose a technique to improve the performance of hierarchical model-based diagnosis, based on structural abstraction. Given a hierarchical representation and the set of currently available observations, the technique is able to dynamically derive a tailored hierarchical representation to diagnose the current situation. We implement our strategy as an extension to the well-known Mozetic's approach [Mozetic, 1992], and illustrate the obtained performance improvements. Our approach is more efficient than Mozetic's one when, due to abstraction, fewer observations are available at the coarsest hierarchical levels.