Default reasoning from conditional knowledge bases: Complexity and tractable cases
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摘要
Conditional knowledge bases have been proposed as belief bases that include defeasible rules (also called defaults) of the form “φ→ψ”, which informally read as “generally, if φ then ψ”. Such rules may have exceptions, which can be handled in different ways. A number of entailment semantics for conditional knowledge bases have been proposed in the literature. However, while the semantic properties and interrelationships of these formalisms are quite well understood, about their computational properties only partial results are known so far. In this paper, we fill these gaps and first draw a precise picture of the complexity of default reasoning from conditional knowledge bases: Given a conditional knowledge base KB and a default φ→ψ, does KB entail φ→ψ? We classify the complexity of this problem for a number of well-known approaches (including Goldszmidt et al.'s maximum entropy approach and Geffner's conditional entailment), where we consider the general propositional case as well as natural syntactic restrictions (in particular, to Horn and literal-Horn conditional knowledge bases). As we show, the more sophisticated semantics for conditional knowledge bases are plagued with intractability in all these fragments. We thus explore cases in which these semantics are tractable, and find that most of them enjoy this property on feedback-free Horn conditional knowledge bases, which constitute a new, meaningful class of conditional knowledge bases. Furthermore, we generalize previous tractability results from Horn to q-Horn conditional knowledge bases, which allow for a limited use of disjunction. Our results complement and extend previous results, and contribute in refining the tractability/intractability frontier of default reasoning from conditional knowledge bases. They provide useful insight for developing efficient implementations.
论文关键词:Reasoning under uncertainty,Conditional knowledge bases,Default reasoning,Nonmonotonic inference,Computational complexity,Polynomial-time algorithms,Horn knowledge bases and variants
论文评审过程:Received 24 April 2000, Available online 28 November 2000.
论文官网地址:https://doi.org/10.1016/S0004-3702(00)00073-4