Highly-sensitive measure of complexity captures Boolean networks’ regimes and temporal order more optimally

In this work, several random Boolean networks (RBNs) are generated and analyzed based on two fundamental features: their time evolution diagrams and their transition diagrams. For this purpose, we estimate randomness using three measures, among which Algorithmic Complexity stands out because it can...

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Bibliographic Details

Published in:	Physica. D Vol. 482; p. 134844
Main Authors:	de J. Luevano-Robledo, Manuel, Puga-Candelas, Alejandro
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.11.2025
Subjects:	Algorithmic complexity Compressibility Entropy Perturbation analysis Random Boolean networks Algorithmic complexity Entropy Compressibility Perturbation analysis Random Boolean networks
ISSN:	0167-2789
Online Access:	Get full text
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