Efficient foraging strategies in multi-agent systems through curve evolutions

Musad Haque, Amir Rahmani, Magnus Egerstedt, Anthony Yezzi

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

In nature, communal hunting is often performed by predators charging through an aggregation of prey. Variations exist in the geometric shape of the charging front depending on the particulars of the feeding strategy. Inspired by biology, this technical note investigates these geometric variations, and we model the predator front as a curve moving through a prey density. Using variational arguments for evolving the curve shape, we optimize the shape of the front.

Original languageEnglish
Article number2281877
Pages (from-to)1036-1041
Number of pages6
JournalIEEE Transactions on Automatic Control
Volume59
Issue number4
DOIs
StatePublished - Jan 1 2014

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Multi agent systems
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Keywords

  • Bio-inspired methods
  • curve evolutions
  • multi-agent foraging

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Computer Science Applications

Cite this

Efficient foraging strategies in multi-agent systems through curve evolutions. / Haque, Musad; Rahmani, Amir; Egerstedt, Magnus; Yezzi, Anthony.

In: IEEE Transactions on Automatic Control, Vol. 59, No. 4, 2281877, 01.01.2014, p. 1036-1041.

Research output: Contribution to journalArticle

Haque, Musad ; Rahmani, Amir ; Egerstedt, Magnus ; Yezzi, Anthony. / Efficient foraging strategies in multi-agent systems through curve evolutions. In: IEEE Transactions on Automatic Control. 2014 ; Vol. 59, No. 4. pp. 1036-1041.
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