Strategy evolution on temporal hypergraphs

Fuente: arXiv
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Autores principales: Wang, Xiaochen, Zhou, Lei, McAvoy, Alex, Tian, Zhenglong, Li, Aming
Formato: Preprint
Publicado: 2023
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author Wang, Xiaochen
Zhou, Lei
McAvoy, Alex
Tian, Zhenglong
Li, Aming
author_facet Wang, Xiaochen
Zhou, Lei
McAvoy, Alex
Tian, Zhenglong
Li, Aming
contents Individuals interact and cooperate in structured systems. Many studies represent this structure using static networks, where each link represents a permanent connection between two nodes. However, real interactions are generally not time-invariant and are often not pairwise. Recently, progress has been made in modeling higher-order interactions using hypergraphs, where a link may connect more than two individuals. Here, we study cooperation on temporal hypergraphs, capturing the time-varying, higher-order interactions seen in empirical systems. We find that temporal hypergraphs can promote cooperation compared with static networks, and the latter may even underestimate the cooperation-boosting effects of constrained, local interactions. We further show that cooperation can be facilitated by temporal hypergraphs with sparse components and higher-order interactions. Importantly, when the size of group interactions (hyperedges) is comparable to the population size, relatively small hyperedge sizes best facilitate cooperation. Synthetic and empirical hypergraphs alike affirm our findings, illuminating how temporal, higher-order interactions profoundly shape the evolution of cooperation.
format Preprint
id arxiv_https___arxiv_org_abs_2306_01300
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Strategy evolution on temporal hypergraphs
Wang, Xiaochen
Zhou, Lei
McAvoy, Alex
Tian, Zhenglong
Li, Aming
Physics and Society
Individuals interact and cooperate in structured systems. Many studies represent this structure using static networks, where each link represents a permanent connection between two nodes. However, real interactions are generally not time-invariant and are often not pairwise. Recently, progress has been made in modeling higher-order interactions using hypergraphs, where a link may connect more than two individuals. Here, we study cooperation on temporal hypergraphs, capturing the time-varying, higher-order interactions seen in empirical systems. We find that temporal hypergraphs can promote cooperation compared with static networks, and the latter may even underestimate the cooperation-boosting effects of constrained, local interactions. We further show that cooperation can be facilitated by temporal hypergraphs with sparse components and higher-order interactions. Importantly, when the size of group interactions (hyperedges) is comparable to the population size, relatively small hyperedge sizes best facilitate cooperation. Synthetic and empirical hypergraphs alike affirm our findings, illuminating how temporal, higher-order interactions profoundly shape the evolution of cooperation.
title Strategy evolution on temporal hypergraphs
topic Physics and Society
url https://arxiv.org/abs/2306.01300