CS 420/594: Advanced Topics in Machine Intelligence
Fall 2003: 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:
Junlong Zhao
Phone: 974-3842
Office: 110I Claxton Complex
Hours: 1:00-2:30 MW, or
make an appointment
Email: zhao@cs.utk.edu
Classes: 3:40-4:55 MW in Cl 205
Directory
of Handouts, Labs, etc.
Directory of Software, including Unix programs from CBN
This page: http://www.cs.utk.edu/~mclennan/Classes/420
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 2003 the topic for my 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, multi-agent systems, and evolutionary
systems.
Prerequisites
To be determined, but I anticipate the following:
Students taking the couse for graduate credit should have 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
I currently anticipate that your grade will be based
on a series of projects, in which you will conduct and
write up experiments using the software associated with Flake's
book, as well as conducting experiments with software that you program yourself.
Students taking CS 594 (i.e. the course for graduate credit) will be
expected to do specified additional work.
Subject to change!
Text
CS 420 & 594: Flake, Gary William. The Computational Beauty of Nature. MIT Press, 1998. See also the book's online webpage (including software).
CS 594: Bar-Yam, Yaneer. Dynamics of Complex Systems.
Perseus, 1997. This book is available online in
pdf format.
Tentative List of Topics
(Chapter numbers refer to Flake unless otherwise specified. Note:
html version of slides may have glitches when viewed with Unix Netscape, but
it's readable.)
- Overview: course description, the complex systems field, complex
systems, emergence, complexity, methods
Lectures 1 [pdf, html], 2 [pdf, html]
- Cellular Automata: Wolfram's classification, Langton's lambda, CA models in nature (ch. 15)
Lectures 3 [pdf, html], 4 [pdf, html], 5 [pdf, html], 6 [pdf, html]
- Autonomous Agents and Self-Organization: termites, ants, flocks, herds, and schools (ch. 16)
Lectures 7 [pdf, html], 8 [pdf, html], 9 [pdf, html], 10 [pdf, html], 11 [pdf, html], 12 [pdf, html], 13 [pdf, html], 14 [pdf, html]
Some links on synchronized fireflies in the Smoky Mountains:
Links on flocking & schooling behavior:
- Competition and Cooperation: zero- and nonzero-sum games, iterated prisoner's dilemma, stable strategies (ch. 17)
Lectures 15 [pdf, html], 16 [pdf, html], 17 [pdf, html]
Some useful links
- Natural and Analog Computation: artificial neural nets, associative memory, Hebbian learning, Hopfield networks (ch. 18)
Lectures 18 [pdf (89 MB), html], 19 [pdf, html], 20 [pdf, html], 21 [pdf, html], 22 [pdf, html]
- Complex Systems & Phase Transitions: summary (ch. 19)
- Genetics and Evolution: biological adaptation & evolution, genetic algorithms, schema theorem (ch. 20)
Lectures 23 [pdf, html], 24 [pdf, html], 25 [pdf, html] - Neural Networks and Learning: pattern classification & linear
separability, single- and multilayer perceptrons, backpropagation,
internal representation (ch. 22)
Lectures 26 [pdf, html], 27 [pdf, html]
- Adaptation: summary (ch. 23)
Lecture 28 [pdf, html]
As time permits:
- Nonlinear Dynamics in Simple Maps (ch. 10)
- Strange Attractors (ch. 11)
- Producer-Consumer Dynamics (ch. 12)
- Controlling Chaos (ch. 13)
- Chaos, Randomness, and Computability (ch. 14)
We will do about one topic every week or so.
Projects/Assignments
Simulators
- CBN Programs
You can run most of these as applets from the Website for Flake's textbook. You can also download sources and executable from there. Some of these are already available in the experiments/CBN subdirectory. The Unix executables are in experiments/CBN/cbn/code/bin.
- Starlogo Programs
You are supposed to be able to run
StarLogo programs as Java applets. To do this, click on their
name below. However, they don't seem to run on all browsers
(perhaps due to different versions of JRE). If anyone can figure
out why, let me know. Also beware that if you are running
StarLogo over a slow connection, it will have to download the starlogo
applet (1.3MB). If you have downloaded a StarLogo system, you can
also download the programs (.slogo files) directly from the experiments directory.
- SlimeSpiral - spiral formation by slime molds
- SlimeStream - streaming aggregation by slime molds
- Pattern - pattern formation by activation & inhibition
- termites - Resnick's termite (or "turmite") simulation
- ResnickAnts - Resnick's ant foraging simulation
- firefly - synchronized firefly flashing
- Flock - coordinated movement of a flock of birds or school of fish
Online Resources
Return to MacLennan's home page
Send mail to Bruce MacLennan / MacLennan@cs.utk.edu
Last updated: December 1, 2003