2013/03/27 by Moises Goldszmidt, Judea Pearl, Goldszmidt, Moises +1
Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #cs.AI
paper · pdf · doi:10.48550/arxiv.1304.1507
Appears in Proceedings of the Fifth Conference on Uncertainty in Artificial Intelligence (UAI1989)
arxiv created 2013/03/27 · arxiv updated 2013/04/08
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.