Thesis Topics

We have a supply of interesting research questions that can be investigated in the scope of a Bachelor's or Master's thesis; the same goes for other research modules. In the following we list some of our areas of research or topics that are suitable to be explored by students' work. If you are an interested student we gladly present available topics more in-depth to you. Please also check the German version of this page, as topics are not automatically linked but are in almost all cases available in both German and English. Besides that, there is also the possibility of coming to us with research ideas of your own. This might be totally different topics as well as topics that fit individual researchers foci or current research agenda but are not explicitly listed here.


If one of the proposed topics caught your mind, don't hesitate to approach the person assigned to it. If you are undecided, are interested in Organic Computing in general or have an idea of your own, please get in touch with Prof. Dr. Hähner directly.

Learning Classifier Systems

  • Approaches to fix overgeneralization in strength-based LCS (Master's thesis, contact: David Pätzel)
  • Lambda calculus–based Genetic Programming with implementation in Haskell (Master’s or possibly Bachelor’s thesis, contact: David Pätzel)
  • Hyperparameter-free Genetic Algorithms in evolutionary Machine Learning / Pittsburgh LCS (Master’s thesis, contact: Michael Heider)

  • Matching in evolutionary Machine Learning / Pittsburgh LCS (Bachelor’s or Master’s thesis, contact: Michael Heider)

  • Local Models in evolutionary Machine Learning / Pittsburgh LCS for function approximation (Bachelor’s oder Master’s thesis, contact: Michael Heider)

Further Topics

There is a large body of further topics available for prospective students. However, as keeping two pages up to date manually can be problematic some times, they are mostly found on the German version of this page ( All topics listed there are usually also available for English speaking students. Please refer to the topics there and contact the employees indicated directly for further information. DeepL usually gives a good first impression on what keywords to search for should you want to do prior research.