A theory of diagnosis from first principles
Artificial Intelligence
Artificial Intelligence
On the relationship between circumscription and negation as failure
Artificial Intelligence
Characterizing diagnoses and systems
Artificial Intelligence
Reasoning with minimal models: efficient algorithms and applications
Artificial Intelligence
Stable model checking made easy
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
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The problem of computing X-minimal models, that is, models minimal with respect to a subset X of all the atoms in a theory, is very relevant for computing circumscriptions and diagnosis. Unfortunately, the problem is NP-hard. In this paper we present two novel algorithms for computing X-minimal models. The advantage of these new algorithms is that, unlike existing ones, they are capable of generating the models one by one. There is no need to compute a superset of all minimal models before finding the first X-minimal one. Our procedures may use local serach techniques, or, alternatively, complete methods. We have implemented and tested the algorithms and the preliminary experimental results are encouraging.