Authors:
Gianfranco Lamperti
;
Federica Vivenzi
and
Marina Zanella
Affiliation:
Università di Brescia, Italy
Keyword(s):
Similarity-based diagnosis, discrete-event systems, temporal observations, subsumption.
Related
Ontology
Subjects/Areas/Topics:
Applications of Expert Systems
;
Artificial Intelligence and Decision Support Systems
;
Enterprise Information Systems
;
Verification and Validation of Knowledge-Based Systems
Abstract:
Similarity-based diagnosis of large active systems is supported by reuse of knowledge generated for solving previous diagnostic problems. Such knowledge is cumulatively stored in a knowledge-base, when the diagnostic session is over. When a new diagnostic problem is to be faced, the knowledge-base is queried in order to possibly find a similar, reusable problem. Checking problem-similarity requires, among other constraints, that the observation relevant to the new problem be subsumed by the observation relevant to the problem in the knowledge-base. However, checking observation-subsumption, following its formal definition, is time and space consuming. The bottleneck lies in the generation of a nondeterministic automaton, its subsequent transformation into a deterministic one (the index space of the observation), and a regular-language containment-checking. In order to speed up the diagnostic process, an alternative technique is proposed, based on the notion of coverage. Besides being
effective, subsumption-checking via coverage is also efficient because no index-space generation or comparison is required. Experimental evidence supports this claim.
(More)