CLASSES OF INTEREST TO STUDENTS WHO WORK IN ROBOTICS
PORTLAND STATE UNIVERSITY Winter 2000
Systems Science Ph.D. Program MW 4:00-5:50
Professor Martin Zwick& SB2, room 104
725-4987 zwick@sysc.pdx.edu
see http://www.sysc.pdx.edu/struct.html
SySc 551/651: DISCRETE MULTIVARIATE MODELING
In the course schedule, the course is called "General Systems & Cybernetics-I"
This course focuses on information theory as a modeling framework and as a
tool for discrete multivariate analysis. The course presents set- and
information-theoretic methods for studying static or dynamic (time series)
relations among qualitative variables or among quantitative variables having
unknown nonlinear relationships. In the "general systems" literature, this
is known as "reconstructability analysis" (RA). RA overlaps partially with
log-linear statistical techniques widely used in the social sciences; both
are especially valuable in data-rich applications (but RA is not exclusively
statistical). RA is highly relevant to the many interrelated "projects"
which go under the names of data-mining, machine learning, knowledge
discovery and representation, etc.
Applied to data analysis, RA allows the decomposition and compression of
multivariate probability distributions (contingency tables) and set-theoretic
relations (and mappings), as well as the composition of multiple
distributions/relations. The methods are very general. They are valuable
in the natural and social sciences and in engineering, business, or other
professional fields whenever categorical variables are useful or linear
models are inadequate. Applied to the conceptualization of "structure"
and "complexity," these set- and information-theoretic ideas are foundational
for systems science.
Prerequisites: Background in probability/statistics. SySc 511 is desirable but not essential.
TEXTS (1-2 at bookstore; 3 [packet] at Smart Copy, 1915th SW 6th Ave, 227-6137)
1. Krippendorff, Klaus (K). Information Theory: Structural Models for
Qualitative Data. Series: Quantitative Applications in the Social Sciences,
Paper # 62, Sage Publications, Beverly Hills, California, 1986.
(ISBN 0-8039-2132-2, paperback)
2. Knoke, David and Burke, Peter J. (K & B). Log-Linear Models. Series:
Quantitative Applications in the Social Sciences, paper # 20. Sage
Publications, Beverly Hills, California, 1980. (ISBN 0-8039-1492-X, paperback)
3. Xeroxed articles and selections from books.
Grades will be based on midterm and final exams and either a computational
project (e.g., data analysis using DMM software or software development)
or a theory-exploring paper.
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PORTLAND STATE UNIVERSITY Winter 2000
Systems Science Ph.D. Program MW. 2:00-3:50
Professor Martin Zwick& SB2, room 104
725-4987 zwick@sysc.pdx.edu
see http://www.sysc.pdx.edu/alife.html
A R T I F I C I A L L I F E
(SySc 557/657 but listed in Winter schedule as 510/610)
"Artificial Life" (ALife) is a name given to theoretical, mathematical, and
computationally "empirical" studies of phenomena commonly associated with
"life," such as replication, metabolism, morphogenesis, learning, adaptation,
and evolution. It focuses on the materiality-independent, i.e., abstract,
bases of such phenomena. As such, it overlaps extensively with "theoretical
biology" and, less extensively, with certain areas of physics and chemistry
and the social sciences. It also raises important philosophical questions.
It is part of a larger research program into "complex adaptive systems," one
stream of contemporary systems theory.
In its intersection with computer science, ALife is the newest example of
"the sciences of the artificial" (Herbert Simon). ALife is to life what AI
is to intelligence. Christopher Langton writes that "Artificial Life ...
complements the traditional biological sciences ... by attempting to
synthesize life-like behaviors within computers and other artificial media."
The purpose is 2-fold: to understand these phenomena better and to develop
new computational technologies.
The course will sample the research literature in this field, and will be
organized in a seminar format. Topics emphasized are: (1) cellular automata
(& other discrete dynamical models), (2) ecological & evolutionary simulations,
and (3) genetic algorithm optimization and adaptation. Other topics include:
artificial chemistry (metabolism & origins of life) and philosophical issues.
TEXTS:
1. Christopher Langton, Charles Taylor, J. Doyne Farmer, Steen Rasmussen, ed.,
Artificial Life II, Santa Fe Institute Studies in the Sciences of Complexity.
Addison-Wesley, New York, 1992. (0-201-52571-2 Paperback)
2. Christoph Adami, Richard K. Belew, Hiroaki Kitano, Charles Taylor, ed.,
Artificial Life VI, Proceedings of the Sixth International Conference on
Artificial Life, MIT Press, Cambridge, 1998. (ISBN 0-262-51099-5 Paperback)
3. Xeroxed articles (to be distributed)
PREREQUISITES: Graduate status or consent of instructor
COURSE WORK: term paper or project; class participation.
&Guest participation of Professor Mark Bedau, Dept. of Philosophy, Reed
College, & Adjunct Professor of Systems Science, PSU