Technical University of Munich, Department of Computer
Science
MQM Paper:
[Dressler/Struss 92b]
Oskar Dressler, Peter Struss
Back to Defaults: Characterizing and Computing Diagnoses as Coherent Assumption Sets
In: Proceedings of the 10th European Conference on Artificial Intelligence (ECAI-92), Vienna, August 3-7, 1992.
Abstract
We define preferred diagnoses as a generalization of minimal diagnoses and characterize them in default logic. Even more important, we show how preferred diagnoses can be computed such that preference checking is interleaved with generation of diagnoses. Moreover, we discuss the use of abductive diagnosis criteria for selecting "explaining" diagnoses among the preferred ones.
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