Exploring Complexity in Science and Technology

CS 346U / SySc 346U:
Computer Science, Systems Science, and University Studies
Fall Quarter 2011

Time : Tuesdays and Thursdays, 10:00-11:50am

Location: Fourth Avenue Building (FAB), Room 40-06.

Instructor: Melanie Mitchell, FAB 120-24, (503) 725-2412, e-mail
Office hours: Tu,Th 3:00-4:00pm, or by appointment.

Course Website: :

Course description: This course introduces the main ideas 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.

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

Homework: Weekly reading assignments; reading questions; 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.

Exams: No exams.

Grading: Homework 60%. Final project: 40%.

Syllabus (subject to change):


Class Topic(s)

Homework and Reading

Tuesday Sept. 27

Class introduction

What is Complexity?

Dynamics, Chaos, and Prediction

Introduction to NetLogo

Here are the Intro slides: pptx or pdf

Here are the links to the videos:
Ants video
Brain video
Immune system video

Week 1 reading: Textbook, Chapters 1-2

Week 1 homework , due Tuesday Oct. 4

Download Netlogo:

Netlogo User Manual (pdf)

Here is the Netlogo program we wrote in class: Examples.nlogo

Thurs. Sept. 29

Dynamics, Chaos, and Prediction, continued

Introduction to NetLogo, continued

Here are the Dynamics and Chaos slides: pptx or pdf

Here is LogisticMap.nlogo

Tues. Oct. 4

Information theory

Here are the Information slides: pptx or pdf

Here is InformationContent.nlogo

Here is the schedule for doing projects

Week 2 reading: Textbook, Chapters 3-4

Week 2 homework , due Tuesday Oct. 11

Thurs. Oct. 6


Here are the Computation slides: pptx or pdf

Tues. Oct. 11

Computation, continued


Here are the Evolution slides (part 1): pptx or pdf

Week 3 reading: Textbook Chapters 5-6

Week 3 homework , due Tuesday Oct. 18

Here is the Netlogo exercise, due Thursday, Oct. 20.

Thurs. Oct. 13

Evolution, continued

Here are the Evolution slides (part 2): pptx or pdf

Tues. Oct. 18

Defining and measuring complexity

Here are the Defining and Measuring Complexity slides: pptx or pdf

Week 4 reading:
Textbook Chapter 7

S. Lloyd, The Calculus of Intricacy (password protected)

Week 4 homework , due Tues. Oct. 25

Thurs. Oct. 20

Guest lecture: Jeff Fletcher, Systems Science Program

Here are the slides.

Tues. October 25

Genetic algorithms

Here are the L-Systems slides: pptx or pdf

Here are the genetic algorithms slides: pptx or pdf

Week 5 reading: Textbook Chapters 8-9

Week 5 homework , due Thursday November 3.

Here is NewLSystemFractals.nlogo.

Thurs. Oct. 27

Students present project abstracts

Genetic algorithms, continued

Here are the genetic algorithm (part 2) slides: pptx or pdf

Here is Robby.nlogo.

Tues. Nov. 1

Cellular automata

Here are the cellular automata (part 1) slides: pptx or pdf

Week 6 reading: Textbook Chapter 10

Week 6 homework: No homework this week besides reading.

Thurs. Nov. 3

Evolution and computation in networks

Guest lecture: Prof. Christof Teuscher, ECE Dept.

Tues. Nov. 8

Cellular automata, part 2

Here are the cellular automata (part 2) slides: pptx or pdf

Week 7 reading: Textbook Chapters 11-12

Week 7 homework , due Tuesday Nov. 15

Thurs. Nov. 10

Information processing in living systems

Here are the slides: pptx or pdf

Tues. Nov. 15

Prospects of computer modeling I Here are the slides: pptx or pdf

Week 8 reading: Textbook Chapter 14

Week 8 homework, due Tuesday Nov. 22

Handout: Final paper format

Thurs. Nov. 17

Networks, part 1 Here are the slides: pptx or pdf

Tues. Nov. 22

Networks and scaling

Here are the slides: pptx or pdf

Week 9 reading: Textbook Chapters 15-16

No homework this week!

Thurs. Nov. 24

No class (Thanksgiving).

Tues. Nov. 29

Networks and scaling, continued.


Here are the slides: pptx or pdf

Week 10 reading: Textbook, Chapter 17-19

Week 10 homework , due Tuesday Dec. 6.

Final paper due Friday Dec. 9.

Thurs. Dec. 1

Wrap-up; Future of the sciences of complexity

Here are the slides: pptx or pdf

Tues. Dec. 6

No class (finals week).

Thurs. Dec. 8

No class (finals week).