Complexity Explorer Santa Few Institute

Introduction to Complexity (Spring, 2014)

Lead instructor:

This course is no longer in session.

Video Zip Files:

Lecture Slides:


Quizzes and Homework: Note that homework is optional and ungraded.  We will be posting solutions to selected homework assignments.

Unit 1:

Unit 2:

Unit 3:

Unit 4:

Unit 5:

Unit 6:

Unit 7:

  • Unit7Homework.pdf
  • Note that all the NetLogo models are in the Models Library:  go to the Biology section. 

Unit 8:

Unit 9

Unit 10

Optional Readings:


  • M. Mitchell, Complexity:  A Guided Tour.  Parts of the course will roughly follow this book.  The book is a useful companion to the course, but is not required for taking this course.

Unit 1: What is Complexity?

  • W. Weaver, Science and complexity. American Scientist, 36: 536-544, 1948.   A classic article by an influential 20th century scientists/mathematician, on why science should focus on complex systems. 
  • S. Lloyd, Measures of complexity: A non-exhaustive list. IEEE Control Systems Magazine, 7-8, August, 2001.   A list of some mathematical measures of complexity, though without much explanation of what they mean.

Unit 2: Dynamics and Chaos

Unit 3: Fractals

  • Fractal Explorer. An on-line book and other resources for learning about fractals.
  • B. Mandelbrot, The Fractal Geometry of Nature, W.H. Freeman and Co. New York (1983).
  • N. Lesmoir-Gordon and R. Edney, et al. Introducing Fractal Geometry, Icon Books Ltd. (2000).
  • M. Schroeder, Fractals, Chaos, Power Laws. W. H. Freeman and Co. (1991)
  • C. Brown and L. Liebovitch, Fractal Analysis, Series: Quantitative Applications in the Social Sciences, Sage Publications Inc. (2010).

Unit 4: Information, Order, and Randomness

  • Shannon, C.E. (1948), A Mathematical Theory of Communication, Bell System Technical Journal, 27, pp. 379–423 & 623–656, July & October, 1948.  Shannon's original article is tough going in places but is available online here.
  • R.V.L. Hartley, Transmission of Information, Bell System Technical Journal, July 1928
  • J. L. Lebowitz, Boltzmann's entropy and time's arrow. A semi-popular article for people who want to read further about the issues in Unit 4.
  • S. Carroll, From Eternity to Here: The Quest for the Ultimate Theory of Time. A fascinating (if long) book that will bring you up-to-date on current views in physics about the nature of time.
  • T. D. Schneider, Information Theory Primer. A nice, brief primer on Shannon information; readable if you are comfortable with exponents, logarithms, summation signs, and such. Geared towards biologists, so uses genetics as an example.
  • James Gleick, The Information: A History, a Theory, a Flood, New York: Pantheon, 2011.  For general audiences.
  • Thomas M. Cover, Joy A. Thomas. Elements of information theory, 1st Edition. New York: Wiley-Interscience, 1991.  A more advanced textbook on information theory.

Unit 5: Genetic Algorithms

  • There are many excellent online tutorials on genetic algorithms, and several good free software packages.
  • Chapter 9 in Complexity:  A Guided Tour, covers some of the same material covered in the lectures for this unit.
  • Robby the Robot code in C.
  • Link to Karl Sims' papers on evolving computer graphics and virtual creatures.
  • J. H. Holland.  Adaptation in Natural and Artificial Systems.   MIT Press, 1992.  John Holland's classic book, originally published in 1975, that sets out the theoretical basis for genetic algorithms. 
  • K. De Jong, Evolutionary Computation.  MIT Press, 2002.  Somewhat technical textbook on genetic algorithms and other evolutionary computation techniques.
  • M. Mitchell, An Introduction to Genetic Algorithms.  MIT Press, 1996.  Older, fairly short textbook on genetic algorithms

Unit 6: Cellular Automata

  • J. Conway, "What is Life?" Chapter 25 in Berlekamp, E. R.; Conway, J. H.; and Guy, R. K., Winning Ways for Your Mathematical Plays, Vol. 2: Games in Particular 
  • W. Poundstone, The Recursive Universe:  Cosmic Complexity and the Limits of Scientific Knowledge.  An entertaining and enlightening popular science book that tackles big questions about the universe by looking at Conway's Game of Life.
  • Elementary Cellular Automaton from
  • Website for A New Kind of Science

Unit 7: Models of Self-Organization

Unit 8: Models of Self-Organization and Cooperation in Social Systems

Unit 9: Networks

Unit 10: Scaling in Biology and Society