Cellular Automata: Research Towards Industry

1. Front Matter

   Pages I-X

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2. Models and Theory

   1. Front Matter

      Pages 1-1

      PDF

   2. Evolving Two-Dimensional Cellular Automata to Perform Density Classification: A Report on Work in Progress

      • F. Jimenez Morales, J. P. Crutchfield, M. Mitchell

      Pages 3-14

   3. A perimeter-time CA for the queen bee problem

      • Andreas Beckers, Thomas Worsch

      Pages 15-25

   4. Role of Irreducible Processes in Complex Dynamics

      • Toku-Fumi Yamamoto

      Pages 26-37

   5. Coupling Microscopic and Macroscopic Cellular Automata

      • Jörg R. Weimar

      Pages 38-41

   6. Synchronous and Asynchronous Updating in Cellular Automata

      • Birgitt Schönfisch, André de Roos

      Pages 42-46

3. Applications

   1. Front Matter

      Pages 47-47

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   2. Where do Industrial Districts Come From? A Cellular Automata Model of Competition, Cooperation and the Dynamics of Industrial Clusters

      • Ari Ginsberg, Erik Larsen, Alessandro Lomi

      Pages 49-66

   3. 2D and 3D Lattice Gas Techniques for Fluid-Dynamics Simulations

      • C. Borsani, G. Cattaneo, V. De Mattei, U. Jocher, B. Zampini

      Pages 67-79

   4. A Cellular Automata Based Computational Model for the Simulation of Dynamic Properties of Filled Rubber Compounds

      • Stefania Bandini, Giampaolo Giuliani, Massimiliano Magagnini

      Pages 80-91

   5. Recent Advances in Dynamical Models of Biodegradation

      • Roberto Serra, Marco Villani, Domenico Oricchio, Salvatore Di Gregorio

      Pages 92-105

   6. Cellular Automata Approaches for Simulating Rheology of Complex Geological Phenomena

      • G. M. Crisci, S. Di Gregorio, F. P. Nicoletta, R. Rongo, W. Spataro

      Pages 106-116

   7. Evolutionary Cellular Automata for Image Compression

      • Hildemar J. Martínez, José Ali Moreno

      Pages 117-126

   8. Uniform and Non-Uniform Cellular Automata: Some Issues and Case Studies in Computer Vision

      • Giovanni Adorni, Stefano Cagnoni, Monica Mordonini

      Pages 127-138

   9. Linear-Time Recognition of Connectivity of Binary Images on 1-bit Inter-Cell Communication Cellular Automata and Their Related Algorithms

      • Hiroshi Umeo

      Pages 139-145

   10. Border Detection in Digital Images With a Simple Cellular Automata Rule

       • Andrés Scarioni, José Alí Moreno

       Pages 146-156

   11. A Computational Model Based on the Reaction-Diffusion Machine to Simulate Transportation Phenomena: the Case of Coffee Percolation

       • S. Bandini, E. Illy, C. Simone, F. Suggi Liverani

       Pages 157-164

   12. Learning Urban Cellular Automata In A Real World

       • Antonio Colonna, Vittorio Di Stefano, Silvana Lombardo, Lorenzo Papini, Giovanni A. Rabino

       Pages 165-184

   13. A Cellular Automaton Traffic Flow Model for Online-Simulation of Urban Traffic

       • Joachim Wahle, Jörg Esser, Lutz Neubert, Michael Schreckenberg

       Pages 185-193

Cellular Automata (CA), about to enter their fifties, are coming of age, seen by the breadth and quality of CA-related research carried out worldwide, as well as by the appearance of interesting applications to real world problems. The papers collected in this book, presented at ACRI 98 (Third Conference on Cellular Automata for Research and Industry -7-9 October 1998), further demonstrate the vitality of this line ofresearch. Until some years ago, a researcher interested in dynamical modelling of spatially of the partial extended systems had only one language at his disposal, namely that differential equations (PDE). These are wonderful tools to use when an analytical solution can be found or a perturbative approach can provide a good approximation of the observed phenomena. The use of digital computers has enormously expanded the explanatory and predictive power of partial differential equations by allowing one to treat cases which had been outside the scope of a "pen and pencil" approach. However, it has also opened up a way to new formalisms which are able to describe interesting phenomena and are, at the same time, well-suited for digital simulation.

• artificial intelligence
• artificial life
• cognition
• evolution
• knowledge
• learning
• machine vision
• modeling
• neural network
• simulation

• Dipartmento di Scienze dell’Informazione, Università di Milano, Milano, Italy

  S. Bandini

• Montecatini Environmental Research Center, Ravenna, Italy

  R. Serra

• Illycaffè S.p.A., Trieste, Italy

  F. Suggi Liverani

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