Using Network Dynamical Influence to Drive Consensus

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

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


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.

Original languageEnglish (US)
Article number26318
JournalScientific reports
StatePublished - May 23 2016
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General


Dive into the research topics of 'Using Network Dynamical Influence to Drive Consensus'. Together they form a unique fingerprint.

Cite this