Temporal reasoning is specially important for medical expert systems, as the final diagnosis is often strongly affected by the sequence in which the symptoms develop. Current research on time structures in artificial intelligence is reviewed, and a temporal model based on fuzzy set theory is developed. The proposed model allows a simple and natural representation of symptoms, and provides for efficient computation of temporal relationships between symptoms. The applicability of the proposed temporal model to expert systems is demonstrated.
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