RESEARCH FOCI
My main research is directed towards Learning Classifier Systems (especially XCS and its derivatives), a family of versatile evolutionary rule-based machine learning algorithms. One of the main arguments for their application is that they generate models that are more easily interpreted than the models generated by other learning systems such as artificial neural networks. However, we still don't yet fully understand in a formal way how LCS work, that is, which kinds of problems LCS are able to learn exactly and why they can learn them—which weakens the argument for them by quite a bit. Through my work, I want to develop a more formal understanding of LCS and finally prove several assumptions that were, up to now, only validated experimentally.
Other than that, I'm very interested in
Other academic activities
- Future Generation Computer Systems
- IEEE Transactions on Evolutionary Computation
- IEEE Access
- International Journal of Information Technology & Decision Making
CURRICULUM/VITAE
since 2017 | Research Assistant with the chair for Organic Computing |
2015–2017 | Master course in Computer Science at the University of Augsburg |
2011–2015 | Bachelor course in Computer Science and Multimedia at the University of Augsburg |
COURSES / TEACHING
name | semester | type |
---|---|---|
Seminar zu Selbstorganisation in verteilten Systemen | summer semester 2022 | Seminar |
Übung zu Organic Computing II | summer semester 2022 | Übung |
Seminar über Naturanaloge Algorithmen und Multi-Agenten Systeme | summer semester 2022 | Seminar |