Higher-Order Systems

Federico Battiston; Giovanni Petri

doi:10.1007/978-3-030-91374-8

Higher-Order Systems

Federico Battiston (Editor), Giovanni Petri (Editor)

Department of Network and Data Science

ISI Foundation

Research output: Book/Report types › Book › peer-review

Abstract (may include machine translation)

The book discusses the potential of higher-order interactions to model real-world relational systems. Over the last decade, networks have emerged as the paradigmatic framework to model complex systems. Yet, as simple collections of nodes and links, they are intrinsically limited to pairwise interactions, limiting our ability to describe, understand, and predict complex phenomena which arise from higher-order interactions. Here we introduce the new modeling framework of higher-order systems, where hypergraphs and simplicial complexes are used to describe complex patterns of interactions among any number of agents. This book is intended both as a first introduction and an overview of the state of the art of this rapidly emerging field, serving as a reference for network scientists interested in better modeling the interconnected world we live in.

Original language	English
Place of Publication	Cham
Publisher	Springer
Number of pages	433
ISBN (Electronic)	978-3-030-91374-8
ISBN (Print)	978-3-030-91376-2, 978-3-030-91373-1
DOIs	https://doi.org/10.1007/978-3-030-91374-8
State	Published - 2022

Publication series

Name	Understanding Complex Systems

Keywords

Higher-order networks
Topological Data Analysis
Social contagion
Many-body Interactions
Network biology
Synchronization

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10.1007/978-3-030-91374-8

Cite this

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title = "Higher-Order Systems",

abstract = "The book discusses the potential of higher-order interactions to model real-world relational systems. Over the last decade, networks have emerged as the paradigmatic framework to model complex systems. Yet, as simple collections of nodes and links, they are intrinsically limited to pairwise interactions, limiting our ability to describe, understand, and predict complex phenomena which arise from higher-order interactions. Here we introduce the new modeling framework of higher-order systems, where hypergraphs and simplicial complexes are used to describe complex patterns of interactions among any number of agents. This book is intended both as a first introduction and an overview of the state of the art of this rapidly emerging field, serving as a reference for network scientists interested in better modeling the interconnected world we live in.",

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AB - The book discusses the potential of higher-order interactions to model real-world relational systems. Over the last decade, networks have emerged as the paradigmatic framework to model complex systems. Yet, as simple collections of nodes and links, they are intrinsically limited to pairwise interactions, limiting our ability to describe, understand, and predict complex phenomena which arise from higher-order interactions. Here we introduce the new modeling framework of higher-order systems, where hypergraphs and simplicial complexes are used to describe complex patterns of interactions among any number of agents. This book is intended both as a first introduction and an overview of the state of the art of this rapidly emerging field, serving as a reference for network scientists interested in better modeling the interconnected world we live in.

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KW - Topological Data Analysis

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KW - Many-body Interactions

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KW - Synchronization

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Higher-Order Systems

Abstract (may include machine translation)

Publication series

Keywords

Access to Document

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Cite this