Disentangling high-order mechanisms and high-order behaviours in complex systems
arXiv:2203.12041 · doi:10.1038/s41567-022-01548-5
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.
References in corpus (5)
- Networks beyond pairwise interactions: structure and dynamics
- The physics of higher-order interactions in complex systems
- Quantifying High-order Interdependencies via Multivariate Extensions of the Mutual Information
- Network reconstruction and community detection from dynamics
- Towards an extended taxonomy of information dynamics via Integrated Information Decomposition
Cited by in corpus (12)
- Unveiling the higher-order organization of multivariate time series
- Explosive cooperation in social dilemmas on higher-order networks
- Collective dynamics on higher-order networks
- Synergistic signatures of group mechanisms in higher-order systems
- Nonequilibrium physics of brain dynamics
- An information-theoretic approach to hypergraph psychometrics
- Assessing high-order effects in feature importance via predictability decomposition
- Mining higher-order triadic interactions
- Higher-Order Interactions and Their Duals Reveal Synergy and Logical Dependence beyond Shannon-Information
- Quantifying High-Order Interdependencies in Entangled Quantum States
- Latent geometry emerging from network-driven processes
- Higher-order contagion processes in 3.99 dimensions