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New Solutions for the Density Classification Task in One Dimensional Cellular Automata

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Modelling and Implementation of Complex Systems (MISC 2018)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 64))

Abstract

The density classification task is one of the most studied benchmark problems to analyze emergent collective computations resulting from local interactions within cellular automata. Solutions for this task were produced by means of different training methods, in particular the automatic design through evolutionary algorithms. This is tied to the fact that there is still a lack of thorough understanding of computations’ nature within cellular automata, which impedes writing efficient local rules. In this paper, we propose a new procedure for solving the density classification task using handwritten local rules in the case of one dimensional cellular automata of radius r = 4. The experimental results show that the newly designed rules outperform the currently best known solutions. This is important since it helps, on the one hand, to deepen our knowledge about selecting appropriate local rules to solve computational tasks and, to improve our general understanding of computations carried out by cellular automata, on the other hand.

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Author information

Authors and Affiliations

  1. RELA(CS)2 Laboratory, University of Oum El-Bouaghi, Route de Constantine BP 321, 04000, Oum El-Bouaghi, DZ, Algeria

    Zakaria Laboudi

  2. MISC Laboratory, University of Constantine 2, Nouvelle Ville Ali Mendjeli BP 67A, 25100, Constantine, DZ, Algeria

    Salim Chikhi

Authors
  1. Zakaria Laboudi
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  2. Salim Chikhi
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Corresponding author

Correspondence to Zakaria Laboudi .

Editor information

Editors and Affiliations

  1. Faculty of New Information and Communication Technologies, University of Constantine 2, Constantine, Algeria

    Salim Chikhi

  2. Faculty of Technology, GeCoDe Laboratory, University of Saida, Saida, Algeria

    Abdelmalek Amine

  3. Faculty of New Information and Communication Technologies, University of Constantine 2, Constantine, Algeria

    Allaoua Chaoui

  4. Faculty of New Information and Communication Technologies, University of Constantine 2, Constantine, Algeria

    Djamel Eddine Saidouni

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Laboudi, Z., Chikhi, S. (2019). New Solutions for the Density Classification Task in One Dimensional Cellular Automata. In: Chikhi, S., Amine, A., Chaoui, A., Saidouni, D.E. (eds) Modelling and Implementation of Complex Systems. MISC 2018. Lecture Notes in Networks and Systems, vol 64. Springer, Cham. https://doi.org/10.1007/978-3-030-05481-6_7

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