Reasoning in Hybrid Knowledge Bases

01.07.2008 - 31.12.2012
Research funding project
In the last years, Description Logics (DLs) have evolved into a standard formalism for ontologies which describe a domain of interest in different applications areas that involve rich information structure. In particular, in the context of the Semantic Web, DL-based ontologies have been designated via the Web Ontology Language (OWL) as a standard for describing the semantics of complex Web resources, in order to facilitate access by automated agents. Driven by the need to overcome limitations of DLs and to integrate them into applications, recent research focuses on tools and methods to access DL ontologies in a declarative knowledge representation formalisms. Most important are here rule-based languages, which play a dominant role in Databases (as query languages), and in Artificial Intelligence, where advanced such languages are powerful tools for declarative problem solving. Combining the strengths of DLs and rule-based languages in hybrid languages is a very active area of research, and several such languages have emerged in the last years. However, their relations and properties are not yet well understood, and effective and efficient reasoning techniques for them need to be developed. This project tackles these issues and pursues the following main goals. First, to develop novel techniques that allow for effective and efficient reasoning in hybrid knowledge bases that combine DLs and rule-based languages. Since this requires a deep understanding of the sources of complexity and the computational properties of the formalisms, a second main goal is a thorough study of their computational complexity. This involves also to clarify the relationships between the formalisms regarding their expressiveness in detail, which is the third main goal. The expected project outcomes are a detailed picture of the semantic and computational properties of selected hybrid formalisms and of their expressive relationships and capabilities as well as efficient reasoning techniques which advance the state of the art.

People

Project leader

Project personnel

Institute

Grant funds

  • FWF - Österr. Wissenschaftsfonds (National) Austrian Science Fund (FWF)

Research focus

  • Computational Intelligence: 100%

Keywords

GermanEnglish
Kombinierte Regeln und Beschreibende LogikCombining Rules and Description Logics
Non-monotonic Logic ProgrammingNicht-Monotone Logik Programmierung
WissensrepräsentationKnowledge Representation
Query LanguagesAbfragesprachen

Publications