Speaker: Prof. Frank Jäkel (Center for Cognitive Science, TU Darmstadt)

 

Date: Sept. 18th 15:10 - 18:00

 

Room: 二教519 (Teaching Building 2, 519)

 

Abstract: 

 

The first part of the lecture is a basic introduction to probability theory from a Bayesian perspective. We will also discuss how Bayesian inference differs from frequentist inference. In the second part of the course we will discuss why Bayesian Decision Theory provides a good starting point for probabilistic models of perception and cognition. The focus here will be on Rational Analysis and Ideal Observer models that provide an analysis of the task, the environment, the background assumptions and the limitations of the cognitive system under study. We will go through several examples from signal detection to categorization to illustrate the approach.

 

Bio:

 

Prof. Frank J?kel is a full professor at the Center for Cognitive Science, which he helped to build at TU Darmstadt, Germany. His research interests range from visual perception to problem-solving. However, most of the time he studies category learning in humans and machines. Before joining the Centre for Cognitive Science at TU Darmstadt, Prof. J?kel was an assistant professor at the Institute of Cognitive Science at the University of Osnabrück. He was a postdoctoral fellow at MIT and did his doctoral work at the MPI for Biological Cybernetics. He studied Cognitive Science, Neural & Behavioural Sciences, and Artificial Intelligence in Osnabrück, Tübingen, and Edinburgh. Homepage: https://www.psychologie.tu-darmstadt.de/models-of-higher-cognition/mod/mem/frank/index.en.jsp