Examples of approximations in diagnosis based on approximate enteilment

The AI literature contains many de nitions of diagnostic reasoning (such as set-covering, abductive, consistency-based). However, diagnosis should not be seen as a problem with a unique de nition. Instead, there exists a whole space of reasonable notions of diagnosis. These notions can be seen as mutual approximations. We use existing work approximate entailment to de ne notions of approximation in diagnosis. We show how such a notion of approximate diagnosis can be exploited in various diagnostic strategies. We illustrate these strategies by performing diagnosis in a small car domain example.