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<p>Cellular Automata (CA) classification enables the identification of appropriate rules for modeling a scenario. This paper examines the use of Communicability Sequence Entropy (CSE) in network representations of Elementary Cellular Automata (ECA) rules to identify more quantifiable similarities within the Wolfram Classification. Previous studies analyzed network representations of ECA rules using different centrality measures. Using information-theoretic measures for these network representations benefits from three domains: Network Science, Cellular Automata, and Information Theory, offering an alternative viewpoint on CA classification. This study uses network and information-theoretic measures to quantify ECA rule behavior by analyzing perturbation propagation and rule similarity. It finds cohesive groups in Classes 1, 3, and 4, but Class 2 remains inconsistent.</p>

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Investigating how cohesive the ECA rules are within Wolfram’s classification: a preliminary study

  • 期刊论文

  • 发表日期：

    2026年6月2日

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  • Sanchit Baweja,
  • Rinkaj Goyal

摘要

Cellular Automata (CA) classification enables the identification of appropriate rules for modeling a scenario. This paper examines the use of Communicability Sequence Entropy (CSE) in network representations of Elementary Cellular Automata (ECA) rules to identify more quantifiable similarities within the Wolfram Classification. Previous studies analyzed network representations of ECA rules using different centrality measures. Using information-theoretic measures for these network representations benefits from three domains: Network Science, Cellular Automata, and Information Theory, offering an alternative viewpoint on CA classification. This study uses network and information-theoretic measures to quantify ECA rule behavior by analyzing perturbation propagation and rule similarity. It finds cohesive groups in Classes 1, 3, and 4, but Class 2 remains inconsistent.