Special Topics in Computer Science: Cognitive Modeling
Cognitive science represents a confluence of disciplines from computing, machine learning and AI, to Psychology and Sociology.
Computational modeling plays a central role in cognitive science. This course is an introduction to computational models of human cognition.
We will cover the major approaches and architectures, both neural network, symbolic, and heuristic; major theoretical issues; and specific computational models
of a variety of cognitive processes, ranging from low-level (e.g., attention and memory) to higher-level (e.g., language and reasoning).
The emphasis is on implemented computational models and on modeling empirical data.
The aim of this course is for you to develop a basic understanding of the issues surrounding cognitive modeling and acquire
the skills and vocabulary to access current research available.
[11/28/06] Finally posted assignment #3!!!
[10/18/06] Posted assignment #2.
[10/17/06] Major revision of the web page content. Be sure to check it out:
[9/27/06] Posted an updated version of the assignment #1 sheet - I encourage design discussion among
students for this assignment, but each person should hand in their own implementation that can not
- Added rule-based material (you will need to know this for the next programming assignment).
- Added wiki (you should go and add your definition of cognition/cognitive science to the wiki).
- Added all the past class presentations.
[9/25/06] Posted programming assignment #1.
[9/25/06] Posted Deborah's presentation.
[9/17/06] Posted David's and Webb's presentations in the lecture notes section.
[9/15/06] Posted a pdf file of the current reading assignment in the lecture notes for those
folks who are still waiting for their book.
[9/15/06] Posted schedule with names.
[9/8/06] Posted the reading list with schedule...please take a look at select the papers you might be interested in presenting.
[9/1/06] There will be an informational meeting on Thursday 9/7/06 at 6pm in Kelly 102.
Cognitive Modeling, Thad A. Polk and Colleen M. Seifert (Eds.), The MIT Press, 2002, ISBN 0262661160.
Simple Heuristics That Make Us Smart, Gerd Gigerenzer, Peter M. Todd, ABC Research Group, Oxford University Press, 2000, ISBN 0195143817.
Documents of Interest:
NOTE: email submissions are not
acceptable for assignments.
Tyler Hall, Room 251
Office Hours: M11am-12pm, T2:30-3:30pm
email: lutz at inductive-reasoning dot com