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Major in Complex Systems
In general, for an ICP, a student needs 30 credit hours
at 300 level or above. For a major in CSS, a student should
take courses that supply:
- Breadth of knowledge
A student should at least be aquainted with all areas of what people
call Complex Systems Studies, and familiar with the "big names"
and famous models of CSS.
- Quantitative modeling approaches and related techniques
A student should have some skill in using and interpreting
results from the standard techniques used in CSS, including:
A. Mathematical modeling
B. Computer modeling
C. Empirical and statistical analysis
- Depth of knowledge
A student should have more than introductory knowledge
in at least one discipline, area of study, or one approach
to studying Complex Systems.
In order to fulfill these requirements, we suggest the
program of study described below.
For general backgound knowledge and skills:
- Math 115, 116, 215, 217
- Sufficient programming courses to become proficient in
at least one language (C,C++,etc)
- We also strongly recommend some applied statistics course,
e.g., Stat 311 / IOE 365 or similar courses offered in many
departments and schools.
Required CSCS courses
- 501 Introduction to Complex Systems
- 530 Computer Modeling of Complex Systems
Required Math courses
- 316 (Differential Equations) or the equivalent
Of the 7 (7*3 credit) courses remaining, we would suggest
the student select four from one particular area, and
three from the other areas, in the following list:
- Life Sciences (L)
- Physical Sciences / Engineering (P)
- Social Sciences (S)
- Mathematics (M)
Below is a list of candidate courses.
From semester to semester, there are likely to be other courses that could
be used to fulfill the requirements for a CSS major.
Students may petition the Center for the Study of Complex Systems to have
other courses accepted for credit toward the major.
CSCS
----
CSCS 501 Intro to Complex Systems
M CSCS 520 Empirical Analysis
CSCS 530 Intro to Computer Modeling
P CSCS 541 Intro to Dynamical Systems
(Note: Has been tilted toward physics systems.)
Psych
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S Psychology 541: Complex Adaptive Systems.
S Psychology 640 / EECS 695: Neural Models and Psychological Processes.
S Psychology 721: Mathematical Psychology
S Psychology 808: Advances in Reinforcement Machine Learning
S Psychology 808, Section 4: Graduate Seminar on Multi-Level Selection
S Psychology 948: Psychology and Psychophysiology of Consciousness
Pol.Science / Econ / SI
S Pol.Sci. 793: Complexity Theory in the Social Sciences
S SI 611: The Future of Organization in the Age of Information
S SI 888 Compar. Model Meth: Using the computer for Policy Problems
Math / Stats
M Biostatistics 645: Time Series Analysis with Biomedical Applications
M Biostatistics 680: Applications of Stochastic Processes
M Biostatistics 845: Advanced Topics in Time Series Analysis.
M Mathematics 462: Mathematical Models
M Math 463: Mathematical Biology
M Math 558: Applied Dynamical Systems
M Mathematics 658: Differential Equations, Dynamical Systems and Mechanics.
M Statistics 610: Stochastic Chaos Theory
Physics
P Physics 406: Statistical Mechanics
P Physic 413 (CSCS 541): Intro to Dynamical Systems
P Physics 620, 540 and Applied Physics 601: Nonlinear Dynamics &
Complex Systems for Applied Scientists and Engineers
Biology
L Epidemiology 802: The Computer Simulation of Epidemiological Processes.
L Microbiology 525 and Bioengineering 525: Cellular & Molecular Networks
L Physiology 618 and Biostat 618: Compartmental Analysis
L Psychology 808, Section 4: Graduate Seminar on Multi-Level Selection
Comp Science
P EECS 509 and IOE 517: Traffic Modeling
P EECS 598-2: Selected Topics in Intelligent Systems and Control
P EECS 598 - Control of Motion in Animals and Machines
P EECS 661: Discrete Event Systems
IOE
P IOE 474: Simulation
P IOE 574: Simulation Analysis
Misc
Honors 493: Complexity and Emergence
P Rackham 570: Spatio-Temporal Complexity in Science and Engineering

Updated September 1, 2005
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