Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web

Thomas Lukasiewicz
2006 2006 Second International Conference on Rules and Rule Markup Languages for the Semantic Web (RuleML'06)  
Vagueness and imprecision abound in multimedia information processing and retrieval. In this paper, we present an approach to fuzzy description logic programs under the answer set semantics for the Semantic Web, which is an integration of description logics with nonmonotonic logic programs under the answer set semantics (with default negation in rule bodies) that also allows for representing and reasoning with vagueness and imprecision. More concretely, we define a canonical semantics of
more » ... e and stratified fuzzy dl-programs in terms of a unique least model and iterative least models, respectively. We then define the answer set semantics of general fuzzy dl-programs, and show in particular that all answer sets of a fuzzy dlprogram are minimal models, and that the answer set semantics of positive and stratified fuzzy dl-programs coincides with their canonical least model and iterative least model semantics, respectively. Furthermore, we also provide a characterization of the canonical semantics of positive and stratified fuzzy dl-programs in terms of a fixpoint and an iterative fixpoint semantics, respectively.
doi:10.1109/ruleml.2006.12 dblp:conf/ruleml/Lukasiewicz06 fatcat:qorslyeshzfbhbqol5rclbc6dm