Disentangling high-order mechanisms and high-order behaviours in complex systems
Information Theory
2022-03-24 v1 math.IT
Data Analysis, Statistics and Probability
Abstract
Battiston et al. (arXiv:2110.06023) provide a comprehensive overview of how investigations of complex systems should take into account interactions between more than two elements, which can be modelled by hypergraphs and studied via topological data analysis. Following a separate line of enquiry, a broad literature has developed information-theoretic tools to characterize high-order interdependencies from observed data. While these could seem to be competing approaches aiming to address the same question, in this correspondence we clarify that this is not the case, and that a complete account of higher-order phenomena needs to embrace both.
Keywords
Cite
@article{arxiv.2203.12041,
title = {Disentangling high-order mechanisms and high-order behaviours in complex systems},
author = {Fernando E. Rosas and Pedro A. M. Mediano and Andrea I. Luppi and Thomas F. Varley and Joseph T. Lizier and Sebastiano Stramaglia and Henrik J. Jensen and Daniele Marinazzo},
journal= {arXiv preprint arXiv:2203.12041},
year = {2022}
}