Exploring Complexity in Science and Technology

CS 346U / SySc 346U
Computer Science, Systems Science, and University Studies
Fall Quarter 2013

Time : Mondays and Wednesday, 2:00-3:50pm

Location: Cramer Hall (CH), Room 1.

Instructor: Melanie Mitchell, FAB 120-24, (503) 725-2412, e-mail
Office hours: T, Th: 2:00-3:00pm, or by appointment.

Course Website: : http://www.cs.pdx.edu/~mm/ExploringComplexityFall2013/index.html

Course Mailing list: TBA

Course description: This course introduces selected topics in Complex Systems, an interdisciplinary field of research that seeks to explain how large numbers of relatively simple entities organize themselves, without the benefit of any central controller, acting collectively to create patterns, use information, and adapt and learn.

The course will introduce undergraduates, in a largely non-mathematical way, to the the methods and tools of computer-based modeling (using the Netlogo simulation environment), and to front-line research on complexity in several different areas of science, including physics, biology, the social sciences, and computer science. Topics will include areas of current research in complex systems science, including dynamics and chaos, information and computation, life and evolution in nature and in machines, the science of networks, and network structure and information processing in living systems. The focus will be on common principles underlying complexity in natural and technological systems.

This course will be taught concurrently with the Massive Open Online Course "Introduction to Complexity", taught by the same instructor, and we will be using many of the course materials from that online course. However, this course will go into the topics more deeply, and more emphasis will be put on computational exercises and projects than in the online course.

Note: This class cannot be used to fulfill the upper division CS electives requirement for CS majors.

Prerequisites: None

Textbook: M. Mitchell, Complexity: A Guided Tour

Course Work and Homework: Weeky videos, reading, lab assignments, and tests. We will spend considerable time in class working together on the lab assignments.

Final Project: For the final project, each student will create his or her own simulation in Netlogo, design and perform experiments using this simulation, and read at least two published papers related to the topic of the simulation. Each student will write a paper (about 10-20 pages, double-spaced, including figures and references) describing the simulation, related papers, and experimental results. No previous knowledge of Netlogo or programming is necessary; the instructor will spend time in each class teaching the Netlogo language and helping students write and debug their simulations.

Grading: Weekly tests: 30%. Weekly assignments: 30%. Final project: 40%. I reserve the right to make adjustments (up or down) to your grade to reflect your participation and effort in the course.

Syllabus (subject to change):


Class Topic(s)

Reading and Assignments

Monday Sept. 30


Here are the links to the videos:
Ants video
Brain video
Immune system video
What are complex systems? video

Week 1 reading:

  • Complexity: A Guided Tour, Chapter 1
  • W. Weaver, Science and complexity. American Scientist, 36: 536-544, 1948.
Week 1 Assignment: pdf

Wednesday Oct. 2

Introduction to Netlogo, continued

Monday Oct. 7

Dynamics and Chaos

Week 2 reading:

  • Complexity: A Guided Tour, Chapter 2
  • Optional reading: Kadanoff, article, Feigenbaum article
Week 2 Assignment: pdf

Wednesday Oct. 9

Dynamics and chaos, continued

Monday Oct. 14


Week 3 reading:

  • Complexity: A Guided Tour, Chapter 7
Week 3 Assignment: pdf

Wednesday Oct. 16

Fractals, continued

Monday Oct. 21

Information, Order, and Randomness

Week 4 reading:

  • Complexity: A Guided Tour, Chapter 3
  • Optional: Complexity: A Guided Tour, Chapter 4
  • Optional: T. D. Schneider, Information Theory Primer
Week 4 Assignment: pdf

Wednesday Oct. 23

Information, Order, and Randomness, continued

Monday Oct. 28

Evolution and Genetic Algorithms

Final project description

Final project paper format

Example projects zip file

Week 5 reading:

  • Complexity: A Guided Tour, Chapters 5 and 9
Week 5 Assignment: pdf

Week 5 Assignment Addendum: pdf

Wednesday Oct. 30

Genetic Algorithms, continued

Monday Nov. 4

Genetic Algorithms, continued.

Cellular Automata

Week 6 reading: Complexity: A Guided Tour, Chapters 10-11

Week 6 Assignment: pdf

Wednesday Nov. 6

Cellular Automata, continued.

Monday Nov. 11

No Class: Veterans Day

Wednesday Nov. 13

Cellular Automata, continued. Models of Self-Organization

Some ideas for projects

Week 7 reading: Complexity: A Guided Tour, Chapter 12

Week 7 Assignment: pdf

Monday Nov. 18

Class cancelled.

Week 8 reading: Texbook, Chapter 14

Week 8 assignments: pdf

Wednesday Nov. 20

Catch-up day.

Monday Nov. 25

Models of Cooperation in Social Systems

Week 9 assignments: pdf

Week 9 reading: Textbook, Chapter 15-16

Week 9 take-home test: pdf

Wednesday Nov. 27

Self-Organization and Cooperation in Social Systems, continued.

Monday Dec. 2


Week 10 assignments, part 1: pdf

Wednesday Dec. 4

Networks, continued. Class wrap-up: pdf

Monday Dec. 9

No class (finals week).

Wednesday Dec. 11

No class (finals week).

Final project papers due