ArticlePloS one2013
Resilience and controllability of dynamic collective behaviors.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Review
- Robustness of Network Controllability with Respect to Node Removals Based on In-Degree and Out-Degree.Entropy (Basel, Switzerland) · 2023Article
- Entropy and Fractal Techniques for Monitoring Fish Behaviour and Welfare in Aquacultural Precision Fish Farming-A Review.Entropy (Basel, Switzerland) · 2023Review
- Optimal network topology for responsive collective behavior.Science advances · 2019Article
- Effect of Correlations in Swarms on Collective Response.Scientific reports · 2017Article
- Analysis of topological relationships and network properties in the interactions of human beings.PloS one · 2017Article
- Connecting core percolation and controllability of complex networks.Scientific reports · 2014Article
- Influence of the number of topologically interacting neighbors on swarm dynamics.Scientific reports · 2014Article
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Authors and funding
2 authors.
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Abstract
The network paradigm is used to gain insight into the structural root causes of the resilience of consensus in dynamic collective behaviors, and to analyze the controllability of the swarm dynamics. Here we devise the dynamic signaling network which is the information transfer channel underpinning the swarm dynamics of the directed interagent connectivity based on a topological neighborhood of interactions. The study of the connectedness of the swarm signaling network reveals the profound relationship between group size and number of interacting neighbors, which is found to be in good agreement with field observations on flock of starlings [Ballerini et al. (2008) Proc. Natl. Acad. Sci. USA, 105: 1232]. Using a dynamical model, we generate dynamic collective behaviors enabling us to uncover that the swarm signaling network is a homogeneous clustered small-world network, thus facilitating emergent outcomes if connectedness is maintained. Resilience of the emergent consensus is tested by introducing exogenous environmental noise, which ultimately stresses how deeply intertwined are the swarm dynamics in the physical and network spaces. The availability of the signaling network allows us to analytically establish for the first time the number of driver agents necessary to fully control the swarm dynamics.
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