Bilattices and the semantics of logic programming
Journal of Logic Programming
The well-founded semantics for general logic programs
Journal of the ACM (JACM)
Combining explicit negation and negation by failure via Belnap's logic
Selected papers from the international workshop on Uncertainty in databases and deductive systems
Multi-valued logic programming semantics: an algebraic approach
Selected papers from the international workshop on Uncertainty in databases and deductive systems
Combining knowledge with many-valued logics
Data & Knowledge Engineering - Special issue: distributed expertise
Artificial Intelligence
Multivalued stable semantics for databases with uncertain information
Information modelling and knowledge bases VIII
Multivalued stable semantics for databases with uncertain information
Information modelling and knowledge bases VIII
HySpirit - A Probabilistic Inference Engine for Hypermedia Retrieval in Large Databases
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Any-world assumptions in logic programming
Theoretical Computer Science
Annals of Mathematics and Artificial Intelligence
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We address the problem of defining semantics for logic programs in presence of incomplete and contradictory information coming from different sources. The information consists of facts that a central server collects and tries to combine using (a) a set of logical rules, that is, a logic program, and (b) a hypothesis representing the server's own estimates. In such a setting incomplete information from a source or contradictory information from different sources necessitate the use of many-valued logics in which programs can be evaluated and hypotheses can be tested. To carry out such activities we propose a formal framework based on bilattices such as Belnap's four-valued logics. In this framework we work with the class of programs defined by Fitting and we propose hypothesis-based semantics for such programs. We also establish an intuitively appealing connection between our hypothesis testing mechanism, on the one hand, and the well-founded semantics and Kripke-Kleene semantics of Datalog programs with negation, on the other hand.