Angewandte Informatik/Kognitive Systeme
Short portrait Cognitive Systems
In the research domain Cognitive Systems (CogSys) we are concerned with the development of approaches, concepts, and methods for design, description, construction, and analysis of intelligent systems based on cognitive principles. On the one hand, we use findings on cognitive processes as inspiration to create artificial systems ('psychonic'), on the other hand, we are interested in computational modeling of cognitive phenomena. Therefore, in our research we combine empirical studies, development of algorithms, and their testing in different areas of application. Main topics of our group are induction and learning as well as planning and problem solving in single- and multi-agent settings. Especially, we are interested in the inductive synthesis of recursive functional programs from incomplete specifications (e.g., input/output examples) which can be seen as a general approach to learning productive rules from experience. We are interested in comprehensible and explainable artificial intelligence. Consequently, our focus is on symbolic/knowledge-level approaches in machine learning (white box learning). Furthermore, we investigate analogical reasoning as a powerful approach to problem solving and as a special mechanism of knowledge acquisition. Current application areas are diagnostics in industry 4.0, facial expression analysis and classification, cognitive models of concept learning, intelligent tutor systems for mathematics and programming.