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Cellular automata and self-organisation phenomena.

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Title: Cellular automata and self-organisation phenomena.
Authors: Marcovici, Irène1 (AUTHOR)
Source: ESAIM: Proceedings & Surveys. 2025, Vol. 80, p17-25. 9p.
Subjects: Cellular automata, Collective behavior, Dynamical systems, Inverse problems, Neighborhoods
Abstract (English): Cellular automata are dynamical systems for which time and space are discrete. They are used to model the evolution of a set of components, the cells, that interact locally with each other: over time, each cell updates its state according to what it perceives in its neighbourhood. Some cellular automata exhibit a self-organisation behaviour: from an initial disordered state, successive updates of the cells by the local rule lead to the emergence of a macroscopic structure. Conversely, given a desired global behaviour, we can ask ourselves which local rules allow to achieve this collective behavior, in a decentralised way. In this article, we will address several such inverse problems (synchronisation, density classification, self-correction of tilings), and study the influence that the introduction of randomness can have on the dynamics. [ABSTRACT FROM AUTHOR]
Abstract (French): Les automates cellulaires sont des systèmes dynamiques pour lesquels le temps et l'espace sont discrets. Ils permettent de modéliser l'évolution d'un ensemble de composantes, les cellules, interagissant entre elles de manière locale : au cours du temps, chacune actualise son état en fonction de ce qu'elle perçoit dans son voisinage. Certains automates cellulaires exhibent des comportements d'auto-organisation : à partir d'un état initial désordonné, les mises à jour successives des cellules par la règle locale conduisent à l'apparition d'une structure macroscopique. A l'inverse, si l'on souhaite parvenir à un certain comportement global, on peut se demander quelles règles locales permettent de l'atteindre de manière décentralisée. Dans cet article, nous présenterons plusieurs problèmes inverses de ce type (synchronisation, classification de la densité, auto-correction de pavages), en étudiant l'influence que peut avoir l'introduction d'aléa dans les dynamiques. [ABSTRACT FROM AUTHOR]
Copyright of ESAIM: Proceedings & Surveys is the property of EDP Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: <searchLink fieldCode="JN" term="%22ESAIM%3A+Proceedings+%26+Surveys%22">ESAIM: Proceedings & Surveys</searchLink>. 2025, Vol. 80, p17-25. 9p.
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  Data: <searchLink fieldCode="DE" term="%22Cellular+automata%22">Cellular automata</searchLink><br /><searchLink fieldCode="DE" term="%22Collective+behavior%22">Collective behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamical+systems%22">Dynamical systems</searchLink><br /><searchLink fieldCode="DE" term="%22Inverse+problems%22">Inverse problems</searchLink><br /><searchLink fieldCode="DE" term="%22Neighborhoods%22">Neighborhoods</searchLink>
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  Data: Cellular automata are dynamical systems for which time and space are discrete. They are used to model the evolution of a set of components, the cells, that interact locally with each other: over time, each cell updates its state according to what it perceives in its neighbourhood. Some cellular automata exhibit a self-organisation behaviour: from an initial disordered state, successive updates of the cells by the local rule lead to the emergence of a macroscopic structure. Conversely, given a desired global behaviour, we can ask ourselves which local rules allow to achieve this collective behavior, in a decentralised way. In this article, we will address several such inverse problems (synchronisation, density classification, self-correction of tilings), and study the influence that the introduction of randomness can have on the dynamics. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label: Abstract (French)
  Group: Ab
  Data: Les automates cellulaires sont des systèmes dynamiques pour lesquels le temps et l'espace sont discrets. Ils permettent de modéliser l'évolution d'un ensemble de composantes, les cellules, interagissant entre elles de manière locale : au cours du temps, chacune actualise son état en fonction de ce qu'elle perçoit dans son voisinage. Certains automates cellulaires exhibent des comportements d'auto-organisation : à partir d'un état initial désordonné, les mises à jour successives des cellules par la règle locale conduisent à l'apparition d'une structure macroscopique. A l'inverse, si l'on souhaite parvenir à un certain comportement global, on peut se demander quelles règles locales permettent de l'atteindre de manière décentralisée. Dans cet article, nous présenterons plusieurs problèmes inverses de ce type (synchronisation, classification de la densité, auto-correction de pavages), en étudiant l'influence que peut avoir l'introduction d'aléa dans les dynamiques. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of ESAIM: Proceedings & Surveys is the property of EDP Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1051/proc/202580017
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      – Code: eng
        Text: English
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        PageCount: 9
        StartPage: 17
    Subjects:
      – SubjectFull: Cellular automata
        Type: general
      – SubjectFull: Collective behavior
        Type: general
      – SubjectFull: Dynamical systems
        Type: general
      – SubjectFull: Inverse problems
        Type: general
      – SubjectFull: Neighborhoods
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      – TitleFull: Cellular automata and self-organisation phenomena.
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            – D: 01
              M: 09
              Text: 2025
              Type: published
              Y: 2025
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              Value: 80
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