Sensing Enhancement on Complex Networks

Brede, Markus; Moreno, Guillermo Romero

doi:10.1007/978-3-030-93413-2_30

Cited by 1 publication

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“…Studying the effects of a groups' social network topology on its sensing abilities is the main aim of this paper, which is based on a paper presented at the Conference on Complex Networks and their Applications in 2021 [29]. Based on the conference paper, we developed a simplified version of the modelling framework proposed by [22] and use analytical and numerical methods to analyse the sensing abilities of collectives in dynamic environments.…”

Section: Introductionmentioning

confidence: 99%

Sensing Enhancement on Social Networks: The Role of Network Topology

Brede

Moreno

2022

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Sensing and processing information from dynamically changing environments is essential for the survival of animal collectives and the functioning of human society. In this context, previous work has shown that communication between networked agents with some preference towards adopting the majority opinion can enhance the quality of error-prone individual sensing from dynamic environments. In this paper, we compare the potential of different types of complex networks for such sensing enhancement. Numerical simulations on complex networks are complemented by a mean-field approach for limited connectivity that captures essential trends in dependencies. Our results show that, whilst bestowing advantages on a small group of agents, degree heterogeneity tends to impede overall sensing enhancement. In contrast, clustering and spatial structure play a more nuanced role depending on overall connectivity. We find that ring graphs exhibit superior enhancement for large connectivity and that random graphs outperform for small connectivity. Further exploring the role of clustering and path lengths in small-world models, we find that sensing enhancement tends to be boosted in the small-world regime.

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Section: Introductionmentioning

confidence: 99%