Harnessing the Power of Temporal Abstractions in Model-Based Diagnosis of Dynamic Systems

In this paper we extend our previous work in the area of temporal diagnostic reasoning. Based on a logical framework extended by qualitative temporal constraints we show how to describe behavioral models (both consistencyand abductive-based), discuss how to use abstract observations and show how abstract temporal diagnoses are computed. This yields an expressive framework which makes computation and representation independent of the number of observations and timepoints in a temporal setting. An example of hepatitis diagnosis is used throughout the paper.