A spectrum of logical definitions of model-based diagnosis
Computational Intelligence
Modeling uncertain temporal evolutions in model-based diagnosis
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
Diagnostic reasoning across different time points
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Maintaining knowledge about temporal intervals
Communications of the ACM
Dynamic across-time measurement interpretation
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
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In this paper we describe a framework for model-based diagnosis of dynamic systems, which extends previous work in this field by using and expressing temporal uncertainty in the form of qualitative interval relations a la Allen. Based on a logical framework extended by qualitative and quantitative temporal constraints we show how to describe behavioral models (both consistency- and abductive-based), discuss how to use abstract observations and show how abstract temporal diagnoses are computed. This yields an expressive framework, which allows the representation of complex temporal behavior allowing us to represent temporal uncertainty. Due to its abstraction capabilities computation is made independent of the number of observations and time points in a temporal setting. An example of hepatitis diagnosis is used throughout the paper.