The integration of knowledge bases in classical first-order logic (and in particular of ontologies in various description logics) with rule languages rooted in logic programming is receiving considerable attention in the context of current efforts around Semantic-Web languages. Towards this integration we introduce fol-programs, which combine logic programs under the answer set and the wellfounded semantics with first-order logic knowledge bases and which generalize dl-programs, a closely related approach combining description logics with rules. Therefore, we define a syntax and a semantics for fol-programs, namely we define minimal model, strong answer set, weak answer set and well-founded semantics for fol-programs, to properly generalize the semantics of ordinary logic programs to fol-programs. We then show computational properties of fol-programs and prove that fol-programs are more expressive than dl-programs. Finally, we present our implementation of the well-founded semantics of fol-programs based on the deductive database engine Ontobroker and the automated theorem prover for first-order logic Vampire and discuss representative reasoning experiments on it.
Combining First-Order Logic and Logic Programming Using Fol-programs
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Description
The integration of knowledge bases in classical first-order logic (and in particular of ontologies in various description logics) with rule languages rooted in logic programming is receiving considerable attention in the context of current efforts around Semantic-Web languages. Towards this integration we introduce fol-programs, which combine logic programs under the answer set and the wellfounded semantics with first-order logic knowledge bases and which generalize dl-programs, a closely related approach combining description logics with rules. Therefore, we define a syntax and a semantics for fol-programs, namely we define minimal model, strong answer set, weak answer set and well-founded semantics for fol-programs, to properly generalize the semantics of ordinary logic programs to fol-programs. We then show computational properties of fol-programs and prove that fol-programs are more expressive than dl-programs. Finally, we present our implementation of the well-founded semantics of fol-programs based on the deductive database engine Ontobroker and the automated theorem prover for first-order logic Vampire and discuss representative reasoning experiments on it.
This self-contained study is both an introduction to quantification theory and an exposition of new results and techniques in "analytic" or "cut free" methods. The focus is on the tableau point of...
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