This course will review computational models of human cognitive processes with four goals in mind: (1) to learn about the wide variety of approaches to cognitive modeling (e.g., self-organizing nets, multi-layer nets, and backpropogation, production systems, ACT*, EPIC, Soar) and the advantages and disadvantages of each, (2) to study some of the most important cognitive models of specifi c domains (e.g., dual task performance, reasoning, explicit learning, working memory.), (3) to evaluate when cognitive modeling is an appropriate and useful research strategy, and (4) to give students an opportunity to gain hands-on experience in implementing their own cognitive models. Students will be expected to take turns in leading discussion of specifi c papers and to work in groups in implementing a computational model.