Concepts and Categories: Combining Insights from Machine Learning and Experimental Psychology

Speaker: Prof. Frank J?kel (Center for Cognitive Science, TU Darmstadt)

Time:  15:30-17:00 Sept. 27

Place: Room 106 Department of Philosophy

Categorization is a fundamental cognitive ability. Many, if not all, higher cognitive functions, like language or problem-solving, crucially depend on categorization. Therefore, categorization has been studied by cognitive scientists and researchers in artificial intelligence alike. Early machine learning algorithms for categorization were inspired by psychology and neuroscience, but today machine learning is a mature field and more recent methods have been developed far beyond their original cognitive motivations. These methods, in turn, can be used to inform experimental studies of human categorization behavior. I will show several examples of how insights from machine learning can feed back into experimental psychology. This is, however, not a one way route: Cognitive models can still shed light on human conceptual behaviors that currently no computer can emulate. I will argue that a full understanding of concepts and categories will depend on a combination of insights from machine learning and experimental psychology.