Cognitive computing addresses problems characterized by ambiguity and uncertainty, meaning that it is used to handle problems humans are confronted with in everyday life. When developing a cognitive computing system which is supposed to act human-like one cannot rely on automated theorem proving techniques alone, since humans performing commonsense reasoning do not obey the rules of classical logics. This causes humans to be susceptible to logical fallacies, but on the other hand to draw useful conclusions automated reasoning systems are incapable of. Humans naturally reason in the presence of incomplete and inconsistent knowledge, are able to reason in the presence of norms as well as conflicting norms and are able to quickly reconsider their conclusions when being confronted with additional information. The versatility of human reasoning illustrates that any attempt to model the way humans perform commonsense reasoning has to use a combination of many different techniques. This project aims at the construction of a cognitive computing system by modeling aspects of human reasoning like emotions and human interactions. For this, we will extend classical logical reasoning with non-monotonic reasoning like defeasible logic and normative reasoning and combine it with machine learning techniques. This will not only be carried out on a theoretical level. Different components important to model the commonsense reasoning process will be developed and combined to a cognitive computing system which will be tested using benchmarks from commonsense reasoning.
Further information available at: http://corg.hs-harz.de
- April 2018 - March 2021
Source of funding:
- DFG - Deutsche Forschungsgemeinschaft
I have been a research associate at WeST since October 2016. I am currently working in the DFG funded research project CoRg which aims at the construction of a cognitive computing system by modeling aspects of human reasoning like emotions and human interactions. I am also involved in the DFG funded research project EVOWIPE were we develop methods to intentionally forget parts of an ontology.
My research interests include artificial intelligence, in particular commonsense reasoning, the semantic web and logic (especially description logics).
Before joining the Institute for Web Science and Technologies, I was a member of the Artificial Intelligence working group at the University of Koblenz-Landau. In my dissertation, I developed methods for modifying the instance level of description logic knowledge bases and investigated precompilation techniques for description logic knowledge bases.
You can find more information on my homepage.
List of my publications at WeST see below. Further publications, e. g. at http://dblp.uni-trier.de/pers/hd/s/Schon:Claudia.