EECS 644 - Computational Modeling of Cognition
Section: 001
Term: WN 2018
Subject: Electrical Engineering and Computer Science (EECS)
Department: CoE Electrical Engineering and Computer Science
Requirements & Distribution:
Advisory Prerequisites:
Graduate standing.
This course counts toward the 60 credits of math/science required for a Bachelor of Science degree.
May not be repeated for credit.
Primary Instructor:

This course will review computational models of human cognitive processes with four goals in mind:

  • to learn about the wide variety of approaches to cognitive modeling and the advantages and disadvantages of each,
  • to study some of the most important cognitive models of specific cognitive domains,
  • to evaluate when cognitive modeling is an appropriate and useful research strategy, and
  • to give students an opportunity to gain hands-on experience in working with cognitive models.

Students will be expected to take turns in leading discussion of specific papers and to complete modeling assignments that require understanding and modifying existing computational models (these assignments will be designed to be manageable for students who do not have a programming background).

Course Requirements:

Grades will be based on the modeling assignments and on quizzes on the readings. There is no textbook; all readings will be posted on CTools. Students will need to have access to a version of Matlab that includes the Neural Network Toolbox.

Intended Audience:

No data submitted

Class Format:

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EECS 644 - Computational Modeling of Cognition
Schedule Listing
001 (LEC)
MW 11:30AM - 1:00PM
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