CS 410 Top: Interactive Games and Cognition

Credit Hours:	4
Course Coordinator:	N/A
Course Description:	The goal of this research seminar is to gain a deeper understanding of the ways in which computing and information technologies, informaiton theory, machine learning, data mining, and game design impact learning in children. In addition to coverage of the broad principles, a number of specific topics will be addressed, including: (1) information-theoretic measures of a learner's knowledge state; (2) automorphic stuctures in learning styles and problem-solving approaches; (3) interpertation of metacognitive operators in the context of gameplay; (4) measuring indcutive bias in a learner's gameplay; (5) co-evolution in cooperative games; and (6) data mining cognitive profiles. In all cases, we will study formal representations and mathematical models for the underlying concepts and cognitive functions. Empirical work may be done within the Zgame architecture developed by Professor York and his students. Students will have to complete required readings, a seminar presentation, a programming assignment, and a term paper.
Prerequisites:	The ideal student will have introductory knowledge of cognitive science; a strong background in artificial intelligence, machine learning, and data mining; good facility with calculus, linear algebra, and differential equations; significant programming experience in Lisp or some OO language (preferably Java), and familarity with a rule based language (preferably Jess). Interested students lacking the prerequisites should seek permission of the instructor.
Goals:
Textbooks:	Some Suggested Background Readings: K. Salem and E. Zimmerman, The Rules of Play: Game Design Fundamentals, MIT Press, 2004, Cambridge, MA. C. Aldrich, Simulations and the Future of Learning, John Wiley & Sons, 2004, published by Peiffer, An Imprint of Wiley, San Francisco, CA. J.P. Gee, What Video Games Have to Teach Us About Learning and Literacy, Palgrave/Macmillan, 2003, New York. L. Samuelson, Evolutionary Games and Equilibrium Selection, MIT Press, 1997, Cambridge, MA. Anderson, J.R. (1996). ACT: A simple theory of complex cognition. American Psychologist, 51, 355-365.
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CAC Category Credits	Core	Advanced
Data Structures
Algorithms
Software Design
Computer Architecture
Programming Languages

Oral and Written Communications:
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Theoretical Content:
Problem Analysis:
Solution Design: