Knowledge Representation and Reasoning
Intelligent systems are knowledge-based. They rely on formally defined knowledge about the domain of interest, spcified in a knowledge base using logical languages. This allows for using different inference mechanism to derive implicit information from a knowledge base. Furthermore, such algorithms can automatically detect inconsistencies and modelling errors, which is used to assist users when building a knoweldge base.
Juniorprof. Dr. Birte Glimm and Dr. Kazakov represent this area within the institute. The main research focus lies on the development of automated reasoning algorithms and optimisations. These are implemented in tools such as ELK, Konclude, or HermiT. Questions regarding the complexity and the efficient evaluation of ontological query languages constitute a further research topic. Members of the group were actively involved in the development of the Web Ontology Language OWL 2 and the SPARQL 1.1 query language standards within the World Wide Web Consortium (W3C).
Reasoners of the institute are very successful at the OWL Reasoner Evaluation Competitions. In 2014 and 2015 our reasoners ELK und Konclude won all six categories. In 2013 our reasoners won 7 out of 10 categories.
phone: +49 (0)731/50-24125
fax: +49 (0)731/50-24119
University of Ulm
Institute of Artificial Intelligence
building O27, level 4
Students' Theses in the area of Knowledge Representation and Reasoning
Datengenerierung für Ontologien
Erzeugung gleichverteilter Lösungen für SAT-Probleme
Design, Implementierung und Optimierung eines kontinuierlich-sprachlichen automatischen Vermittlungssystems