Uncertainty and Description Logic Programs: A Proposal for Expressing Rules and Uncertainty on Top of Ontologies

Rule-based and object-oriented techniques are rapidly making their way into the infrastructure for representing and reasoning about the Semantic Web and combining these two paradigms emerges as an important objective. We present a new family of representation languages, which extents existing language families for the Semantic Web: namely emph{Description Logic Programs} (DLPs) and DLPs with emph{uncertainty} ($mu$DLPs). The former combine the expressive power of description logics (which capture the meaning of the most popular features of structured representation of knowledge) and disjunctive logic programs (powerful rule-based representation languages). The latter are DLPs in which the management of uncertainty is considered as well. We show that $mu$DLPs may be applied in the context of distributed information search in the Semantic Web, where the representation of the inherent uncertainty of the relationships among resource ontologies, to which an automated agent has access to, is required.