Knowledge Representation and Engineering

Intelligent systems require access to general knowledge about the world and to specific knowledge about the application domain in which they are deployed. The aim of knowledge representation and engineering is to develop languages and formalisms that can be used to represent the knowledge, along with associated reasoning methods and algorithms, as well as engineering tools that support knowledge engineers in capturing actual knowledge when building concrete systems.

At ScaDS.AI Dresden/Leipzig, we carry out cutting-edge research in various aspects of knowledge representation and engineering such as ontology languages, with an emphasis on description logics and rule-based languages, ontology reasoning and algorithms, ontology-mediated access to large and incomplete data, both exact and approximate, knowledge graphs and Wikidata, non-monotonic reasoning, formal argumentation, explanation of the behaviour of knowledge-based systems, and methods for dealing with heterogeneous and diverse knowledge.

Contact

Portrait of Prof. Dr. Carsten Lutz

Prof. Dr. Carsten Lutz

Universität Leipzig

carsten.lutz@uni-leipzig.de

Find out more about our research in the field of AI Algorithms and Methods.

TU
Universität
Max
Leibnitz-Institut
Helmholtz
Hemholtz
Institut
Fraunhofer-Institut
Fraunhofer-Institut
Max-Planck-Institut
Institute
Max-Plank-Institut