Extending the Particle Swarm Algorithm to Model Animal Foraging Behaviour

  • Cecilia Di Chio
  • Riccardo Poli
  • Paolo Di Chio
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4150)

Abstract

The particle swarm algorithm [1] contains elements which map fairly strongly to the group-foraging problem in behavioural ecology: its continuous equations of motion include concepts of social attraction and communication between individuals, two of the general requirements for grouping behaviour [2]. Despite its socio-biological background, the particle swarm algorithm has rarely been applied to biological problems, largely remaining a technique used in classical optimisation problems. In this paper [3], we show how some simple adaptions to the standard algorithm can make it well suited for the foraging problem.

This is a preview of subscription content, log in to check access.

References

  1. 1.
    Kennedy, J., Eberhart, R.C.: Swarm Intelligence. Morgan Kaufmann Publishers, San Francisco (2001)Google Scholar
  2. 2.
    Krause, J., Ruxton, G.D.: Living in Groups. Oxford University Press, Oxford (2002)Google Scholar
  3. 3.
    Di Chio, C., Poli, R., Di Chio, P.: Extending the Particle Swarm Algorithm to Model Animal Foraging Behaviour. University of Essex (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Cecilia Di Chio
    • 1
  • Riccardo Poli
    • 1
  • Paolo Di Chio
    • 2
  1. 1.Department of Computer ScienceUniversity of EssexColchesterUnited Kingdom
  2. 2.Dipartimento di Sistemi e Istituzioni per l’EconomiaUniversity of L’AquilaL’AquilaItaly

Personalised recommendations