Simulating Complex Systems by Cellular Automata

  • Jiri Kroc
  • Peter M.A. Sloot
  • Alfons G. Hoekstra

Part of the Understanding Complex Systems book series (UCS)

Table of contents

  1. Front Matter
    Pages i-xxi
  2. Theory of Cellular Automata

    1. Front Matter
      Pages 17-17
    2. Alfons G. Hoekstra, Jiří Kroc, Peter M.A. Sloot
      Pages 1-16
  3. Theory of Cellular Automata

  4. Applications of Cellular Automata

    1. Front Matter
      Pages 217-217
    2. Wenjian Yu, Dirk Helbing
      Pages 219-239
    3. Halim Kusumaatmaja, Julia M. Yeomans
      Pages 241-274
    4. Debashish Chowdhury, Katsuhiro Nishinari, Andreas Schadschneider
      Pages 275-300
  5. Cellular Automata Software

    1. Front Matter
      Pages 355-355
    2. Domenico Talia, Lev Naumov
      Pages 357-384

About this book


Deeply rooted in fundamental research in Mathematics and Computer Science, Cellular Automata (CA) are recognized as an intuitive modeling paradigm for Complex Systems. Already very basic CA, with extremely simple micro dynamics such as the Game of Life, show an almost endless display of complex emergent behavior. Conversely, CA can also be designed to produce a desired emergent behavior, using either theoretical methodologies or evolutionary techniques. Meanwhile, beyond the original realm of applications - Physics, Computer Science, and Mathematics – CA have also become work horses in very different disciplines such as epidemiology, immunology, sociology, and finance. In this context of fast and impressive progress, spurred further by the enormous attraction these topics have on students, this book emerges as a welcome overview of the field for its practitioners, as well as a good starting point for detailed study on the graduate and post-graduate level. The book contains three parts, two major parts on theory and applications, and a smaller part on software. The theory part contains fundamental chapters on how to design and/or apply CA for many different areas. In the applications part a number of representative examples of really using CA in a broad range of disciplines is provided - this part will give the reader a good idea of the real strength of this kind of modeling as well as the incentive to apply CA in their own field of study.


Dynamics Software automata behavior complexity computer science environment evolution mathematics model modeling physics problem solving quality simulation

Editors and affiliations

  • Jiri Kroc
    • 1
  • Peter M.A. Sloot
    • 2
  • Alfons G. Hoekstra
    • 3
  1. 1.StahlavyCzech Republic
  2. 2.Fac. Science, Informatics InstituteUniversiteit AmsterdamAmsterdamNetherlands
  3. 3., Computational Science FacultyUniversity of AmsterdamAmsterdamNetherlands

Bibliographic information