The case studies in this book were written by students at Olin College, and edited by Lisa Downey and Allen Downey. They were reviewed by a program committee of faculty at Olin College who chose the ones that met the criteria of interest and quality. I am grateful to the program committee and the students.
I invite readers to submit additional case studies. Reports that meet the criteria will be published in an online supplement to this book, and the best of them will be included in future print editions.
The criteria are the following:
The case study should be relevant to complexity. For an overview of possible topics, see http://en.wikipedia.org/wiki/Complexity and http://en.wikipedia.org/wiki/Complex_systems. Topics not already covered in the book are particularly welcome.
A good case study might present a seminal paper, reimplement an important experiment, discuss the results, and explain their context. Original research is not necessary and might not be appropriate for this format, but you could extend existing results.
A good case study should invite the reader to participate by including exercises, references to further reading, and topics for discussion.
The case study should present enough technical detail that the reader could implement the model in a language like Python.
If you use an algorithm or data structure that deserves comment, you should discuss it. Topics not covered in the book, including tree algorithms and dynamic programming, are particularly welcome.
If you use a feature of Python or a module that you think will interest readers, you should discuss it. But you should stick to modules that are in widespread use and either included in Python distributions or easy to install.
For more details, see http://thinkcomplex.com/case_studies.