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Probabilistic sequential diagnosis by compilation

Siddiqi, Sajjad; Huang, Jinbo


When a system behaves abnormally, a diagnosis is a set of system components whose failure explains the abnormality. It is known that compiling the system model into deterministic decomposable negation normal form (d-DNNF) allows efficient computation of the complete set of diagnoses. We extend this approach to sequential diagnosis, where a sequence of measurements is taken to narrow down the set of diagnoses until the actual faults are identified. We propose novel probabilistic heuristics to...[Show more]

CollectionsANU Research Publications
Date published: 2008
Type: Conference paper
Source: Proceedings of The 10th International Symposium on Artificial Intelligence and Mathematics (ISAIM 2008)

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