Computational Cognitive Sciences

Catalog description

This course aims to introduce students to the basic concepts and methodology needed to implement and analyze computational models of cognition. It considers the fundamental issues of using a computational approach to explore and model cognition. In particular, the course explores the way that computational models relate to, are tested against, and illuminate psychological theories and data. The course will introduce both symbolic and subsymbolic modelling methodologies and provide practical experience with implementing models. The symbolic part will focus on cognitive architectures, while the subsymbolic part will introduce probabilistic models. Three credits; two- hour lecture and two-hour laboratory. Prerequisites: AI 260, ENGR 328 and ENGR 341