Extending the particle swarm algorithm to model animal foraging behaviour

Authors:
Cecilia Di Chio;Riccardo Poli;Paolo Di Chio
Affiliations:
Department of Computer Science, University of Essex, Colchester, United Kingdom;Department of Computer Science, University of Essex, Colchester, United Kingdom;Dipartimento di Sistemi e Istituzioni per l’Economia, University of L’Aquila, L’Aquila, Italy
Venue:
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
Year:
2006

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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.