Q580: Intro. To Dynamic Systems In Cognition
My philosophy in this course is to give participants a solid introduction to dynamic systems. Given the massive size of the field and the limited time, we have to carefully select the topics to cover. Because I believe that the student cannot really comprehend nonlinear systems without a pretty thorough understanding of linear systems, that is where we start: first order, 1-dimensional, homogeneous, continuous time, linear systems. As the former indicates, we focus on continuous time systems. If one understands these, it is relatively easy to learn discrete time systems, but the converse is not so true.
School/Department: Psychological and Brain Science
Instructor: J. Townsend and alternately, R. Beer.
Other Contact(s): Jim Townsend - firstname.lastname@example.org
Prerequisites: Introductory differential equations helpful but not mandatory. Otherwise, see items 20-22.
Algebra Required?: Linear algebra and matrix theory. Used for all three.
Calculus Required?: At least two terms of differential and integral calculus. Also used for all three.
Day(s) per week offered: 2 or 3.
Recommended follow-up classes: Advanced undergraduate or grad-level differential equations.
Substantive Orientation: Psychological and biological sciences. Applied and theoretical statistics and quantitative modeling. Computer science, especially HCI and AI
Books used: Boyce & De Prima, Differential Equations; Beltrami, Dynamic Systems; Devaney, Chaos Theory.
How the software is used: Programming and computation.
Problem Sets: Yes.
Data Analysis: Not usually.
Presentations: Not required by invited.
Comments: A paper applying dynamic systems theory to a theoretical research problem of interest to the student.