Using network dynamical influence to drive consensus

Giuliano Punzo, George F. Young, Malcolm Macdonald, Naomi E. Leonard

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Consensus and decision-making are often analysed in the context of networks, with many studies focusing attention on ranking the nodes of a network depending on their relative importance to information routing. Dynamical influence ranks the nodes with respect to their ability to influence the evolution of the associated network dynamical system. In this study it is shown that dynamical influence not only ranks the nodes, but also provides a naturally optimised distribution of effort to steer a network from one state to another. An example is provided where the “steering” refers to the physical change in velocity of self-propelled agents interacting through a network. Distinct from other works on this subject, this study looks at directed and hence more general graphs. The findings are presented with a theoretical angle, without targeting particular applications or networked systems; however, the framework and results offer parallels with biological flocks and swarms and opportunities for design of technological networks.
LanguageEnglish
Article number26318
Number of pages13
JournalScientific Reports
Volume6
DOIs
Publication statusPublished - 23 May 2016

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Dynamical systems
Decision making

Keywords

  • decision making
  • netwoks
  • consensus
  • consensus based decision-making

Cite this

Punzo, Giuliano ; Young, George F. ; Macdonald, Malcolm ; Leonard, Naomi E. / Using network dynamical influence to drive consensus. In: Scientific Reports. 2016 ; Vol. 6.
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Using network dynamical influence to drive consensus. / Punzo, Giuliano; Young, George F.; Macdonald, Malcolm; Leonard, Naomi E.

In: Scientific Reports, Vol. 6, 26318 , 23.05.2016.

Research output: Contribution to journalArticle

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