Combining Semantic Web and Logic Programming for Agent Reasoning

Abstract

Web Ontology Language (OWL) provides means to semantically represent domain knowledge as ontologies. Then, ontological reasoning allows software agents to effectively share and semantically interpret the knowledge. OWL adopts open world semantics and in order to achieve decidability its expressiveness is strictly limited. Therefore, many real-life problems cannot be represented only using ontologies and cannot be solved using just ontological reasoning. On the other hand, traditional reasoning mechanisms for autonomous agents are mostly based on Logic Programming (LP) and closed world assumption. LP provides a very expressive formal language, however it requires domain knowledge to be encoded as a part of logic programs. In this paper, we propose Ontological Logic Programming (OLP), a novel approach that combines logic programming with ontological reasoning. The proposed approach enables the use of ontological terms (i.e., individuals, classes and properties) directly within logic programs. The interpretation of these terms are delegated to an ontology reasoner during the interpretation of the program. Unlike similar approaches, OLP makes use of the full capacity of both the ontological reasoning and logic programming. Using case-studies, we demonstrate the usefulness of OLP in multi-agent settings.