Simulating Complex Systems by Cellular Automata

1. Front Matter

   Pages i-xxi

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2. Theory of Cellular Automata

   1. Front Matter

      Pages 17-17

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3. Introduction to Modeling of Complex Systems Using Cellular Automata

   1. Introduction to Modeling of Complex Systems Using Cellular Automata

      • Alfons G. Hoekstra, Jiří Kroc, Peter M.A. Sloot

      Pages 1-16

4. Theory of Cellular Automata

   1. Front Matter

      Pages 17-17

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   2. Multilevel Cellular Automata as a Tool for Studying Bioinformatic Processes

      • Paulien Hogeweg

      Pages 19-28

   3. Complex Automata: Multi-scale Modeling with Coupled Cellular Automata

      • Alfons G. Hoekstra, Alfonso Caiazzo, Eric Lorenz, Jean-Luc Falcone, Bastien Chopard

      Pages 29-57

   4. Hierarchical Cellular Automata Methods

      • Adam Dunn

      Pages 59-80

   5. Cellular Automata Composition Techniques for Spatial Dynamics Simulation

      • Olga Bandman

      Pages 81-115

   6. Problem Solving on One-Bit-Communication Cellular Automata

      • Hiroshi Umeo

      Pages 117-144

   7. Minimal Cellular Automaton Model of Inter-species Interactions: Phenomenology, Complexity and Interpretations

      • Andrew Adamatzky, Martin Grube

      Pages 145-165

   8. Cellular Evolutionary Algorithms

      • Marco Tomassini

      Pages 167-191

   9. Artificial Evolution of Arbitrary Self-Replicating Structures in Cellular Spaces

      • Zhijian Pan, James A. Reggia

      Pages 193-216

5. Applications of Cellular Automata

   1. Front Matter

      Pages 217-217

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   2. Game Theoretical Interactions of Moving Agents

      • Wenjian Yu, Dirk Helbing

      Pages 219-239

   3. Lattice Boltzmann Simulations of Wetting and Drop Dynamics

      • Halim Kusumaatmaja, Julia M. Yeomans

      Pages 241-274

   4. CA Modeling of Ant-Traffic on Trails

      • Debashish Chowdhury, Katsuhiro Nishinari, Andreas Schadschneider

      Pages 275-300

   5. Lattice-Gas Cellular Automaton Modeling of Emergent Behavior in Interacting Cell Populations

      • Haralambos Hatzikirou, Andreas Deutsch

      Pages 301-331

   6. Cellular Automata for Simultaneous Analysis and Optimal Structural Topology Design

      • Zafer Gürdal, Ramzi Zakhama

      Pages 333-353

6. Cellular Automata Software

   1. Front Matter

      Pages 355-355

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   2. Parallel Cellular Programming for Emergent Computation

      • Domenico Talia, Lev Naumov

      Pages 357-384

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. Finally, we included a smaller section on software, to highlight the important work that has been done to create high quality problem solving environments that allow to quickly and relatively easily implement a CA model and run simulations, both on the desktop and if needed, on High Performance Computing infrastructures.

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

• Stahlavy, Czech Republic

  Jiri Kroc

• Fac. Science, Informatics Institute, Universiteit Amsterdam, Amsterdam, Netherlands

  Peter M.A. Sloot

• , Computational Science Faculty, University of Amsterdam, Amsterdam, Netherlands

  Alfons G. Hoekstra

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