Consensus speed maximisation in engineered swarms with autocratic leaders

Ruaridh Clark, Giuliano Punzo, Kristaps Baumanis, Malcolm Macdonald

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

Control of a large engineered swarm can be achieved by influencing key agents within the swarm. The swarm can rely on its communication network to spread the external perturbation and transition to a new state when all agents reach a consensus. Maximising this consensus speed is a vital design parameter when fast response is desirable. The systems analysed consist of N interacting agents that have the same number of outward, observing, connections that follow k-nearest neighbour rules and are represented by a directed graph Laplacian. The spectral properties of this graph are exploited to identify leaders with a newly presented semi-analytical approach referred to as the Leaders of Influence (LoI) method. This method is demonstrated on k-NNR graphs for a set number of leaders. These methods are compared with a genetic algorithm and are shown to be efficient and effective at leader identification. A focus of this work is the effect of leadership style on consensus speed where an autocratic approach (leaders that are not influenced by other nodes in the graph) is shown to always produce faster consensus than a democratic leadership model.
Original languageEnglish
Title of host publicationProceedings of the International Conference on Artificial Intelligence and Robotics and the International Conference on Automation, Control and Robotics Engineering
Place of PublicationNew York
Number of pages5
DOIs
Publication statusPublished - 13 Jul 2016

Keywords

  • consensus speed
  • swarm engineering
  • network analysis

Fingerprint Dive into the research topics of 'Consensus speed maximisation in engineered swarms with autocratic leaders'. Together they form a unique fingerprint.

  • Cite this

    Clark, R., Punzo, G., Baumanis, K., & Macdonald, M. (2016). Consensus speed maximisation in engineered swarms with autocratic leaders. In Proceedings of the International Conference on Artificial Intelligence and Robotics and the International Conference on Automation, Control and Robotics Engineering New York. https://doi.org/10.1145/2952744.2952765