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Probabilistic Cellular Automata

Theory, Applications and Future Perspectives

  • Pierre-Yves Louis
  • Francesca R. Nardi

Part of the Emergence, Complexity and Computation book series (ECC, volume 27)

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Roberto Fernández, Pierre-Yves Louis, Francesca R. Nardi
    Pages 1-30
  3. Roeland M. H. Merks
    Pages 31-34
  4. Probability and Statistical Mechanics

    1. Front Matter
      Pages 35-35
    2. Emilio N. M. Cirillo, Francesca R. Nardi, Cristian Spitoni
      Pages 37-51
    3. Paolo Dai Pra, Elena Sartori, Marco Tolotti
      Pages 53-67
    4. Antal A. Járai
      Pages 79-88
    5. Pierre-Yves Louis, Ida G. Minelli
      Pages 105-118
  5. Computer Science and Discrete Dynamical Systems

  6. Applications to Natural Sciences and Computational (Cell) Biology

    1. Front Matter
      Pages 237-237
    2. Nazim Fatès, Vincent Chevrier, Olivier Bouré
      Pages 239-259
    3. Sonja E. M. Boas, Yi Jiang, Roeland M. H. Merks, Sotiris A. Prokopiou, Elisabeth G. Rens
      Pages 279-310
    4. Daan Crommelin
      Pages 327-339
  7. Back Matter
    Pages 341-344

About this book

Introduction

This book explores Probabilistic Cellular Automata (PCA) from the perspectives of statistical mechanics, probability theory, computational biology and computer science. PCA are extensions of the well-known Cellular Automata models of complex systems, characterized by random updating rules. Thanks to their probabilistic component, PCA offer flexible computing tools for complex numerical constructions, and realistic simulation tools for phenomena driven by interactions among a large number of neighboring structures. PCA are currently being used in various fields, ranging from pure probability to the social sciences and including a wealth of scientific and technological applications. This situation has produced a highly diversified pool of theoreticians, developers and practitioners whose interaction is highly desirable but can be hampered by differences in jargon and focus. This book – just as the workshop on which it is based – is an attempt to overcome these difference and foster interest among newcomers and interaction between practitioners from different fields. It is not intended as a treatise, but rather as a gentle introduction to the role and relevance of PCA technology, illustrated with a number of applications in probability, statistical mechanics, computer science, the natural sciences and dynamical systems. As such, it will be of interest to students and non-specialists looking to enter the field and to explore its challenges and open issues.

Keywords

high-dimensional interacting stochastic systems dynamical systems multiscale models complex systems individual-based stochastic models agent-based modelling decentralised computational systems synchronous/asynchronous updating resilience to asynchronism density classiffication emergence of collective behaviour self-organisation bootstrap percolation crisis propagation equilibrium and non-equilibrium statistical mechanics phase transition metastability finite range and mean field interactions reaction-diffusion

Editors and affiliations

  • Pierre-Yves Louis
    • 1
  • Francesca R. Nardi
    • 2
  1. 1.Laboratoire de Mathématiques et Applications UMR 7348Université de Poitiers, CNRSPoitiersFrance
  2. 2.University of TechnologyEindhovenThe Netherlands

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-65558-1
  • Copyright Information Springer International Publishing AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-65556-7
  • Online ISBN 978-3-319-65558-1
  • Series Print ISSN 2194-7287
  • Series Online ISSN 2194-7295
  • Buy this book on publisher's site
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