Deciding Consistency of Databases Containing Defeasible and Strict Information

Goldszmidt, Moises, Pearl, Judea

arXiv.org Artificial Intelligence 

We propose a norm of consistency for a mixed set of defeasible and strict sentences, based on a probabilistic semantics. This norm establishes a clear distinction between knowledge bases depicting exceptions and those containing outright contradictions. We then define a notion of entailment based also on probabilistic considerations and provide a characterization of the relation between consistency and entailment. We derive necessary and sufficient conditions for consistency, and provide a simple decision procedure for testing consistency and deciding whether a sentence is entailed by a database. Finally, it is shown that if al1 sentences are Horn clauses, consistency and entailment can be tested in polynomial time.

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