CS 420/594: Advanced Topics in Machine Intelligence
Fall 2002: Complex Systems and Self-Organization
Instructor:
Bruce MacLennan
Phone: 974-5067
Office: 217 Claxton Complex
Hours: 2:00-3:30 MW, or make
an appointment
Email: maclennan@cs.utk.edu
Teaching Assistant:
William E Duncan
Phone: 974-0995
Office: Claxton 224
Hours: T/TH 2:35-3:35p
Email: duncan@cs.utk.edu
Classes: 3:40-4:55 MW in Cl 205
Directory
of Handouts, Labs, etc.
This page:
http://www.cs.utk.edu/~mclennan/Classes/420-594-F02
Information
Description
CS 420 covers advanced topics in machine intelligence with an emphasis
on faculty research; CS 594 is similarly focused on faculty research. In
the Fall semester of 2002 the topic for CS 420/594 will be complex systems
and self-organization.
In emergent computation, information processing emerges from
the parallel interaction of large numbers of comparatively simple computational
units. Emergent computation is increasingly important as we seek to increase
the power and robustness of computational systems by increased use of parallelism
and by the exploitation of innovative computational technologies (optical,
molecular, biological, etc.). Fundamental to the theory and implementation
of emergent computation systems is an understanding of the behavior and
self-organization of complex systems: systems in which the interaction
of the components is not simply reducible to the properties of the components.
This project-oriented course will focus on natural and artificial complex
systems, including neural networks, cellular automata, and evolutionary
systems.
Prerequisites
To be determined, but I anticipate the following:
Basic calculus through differential equations (e.g. Mat 231, 241),
linear algebra (e.g. Mat 251), probability and statistics (e.g. Mat 323).
Note!
Take these prerequisites seriously! You will need these skills to understand
the material, to do the homework and to do the projects.
Grading
To be determined.
Students taking CS 594 (i.e. the course for graduate credit) will be
expected to do specified additional work.
Subject to change!
Text
Bar-Yam, Yaneer. Dynamics of Complex Systems. Perseus,
1997. This book is
available
online in pdf format.
Tentative List of Topics
-
Overview (course description, the complex systems field, complex systems,
emergence, complexity, methods)
-
Neural Networks I (attractor net, feedforward nets, subdivided nets)
-
Neural Networks II (brain function & models of mind)
-
Life I: Evolution (origins of complex organisms, exploration, optimization,
selection)
-
Life II: Developmental Biology (differentiation, mathematical theories,
self-organization, pattern formation)
-
Human Civilization I (defining & measuring complexity)
-
Human Civilization II (human civilization as a complex system)
As time permits:
-
Protein Folding I (size scaling, parallel processing, homogeneous &
inhomogeneous systems)
-
Protein Folding II (polymer dynamics)
We will do about one topic every two weeks.
Projects/Assignments
Online Resources
Return to MacLennan's home page
Send mail to Bruce MacLennan / MacLennan@cs.utk.edu
Last updated:
Sat Dec 14 16:40:33 EST 2002