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ANTSW
2006
Springer

Extending the Particle Swarm Algorithm to Model Animal Foraging Behaviour

8 years 8 months ago
Extending the Particle Swarm Algorithm to Model Animal Foraging Behaviour
The particle swarm algorithm contains elements which map fairly strongly to the foraging problem in behavioural ecology. In this paper, we show how some simple adaptions to the standard algorithm can make it well suited for the foraging problem. We propose two approaches to model foraging behaviour: the first uses a standard particle swarm algorithm, with the particles just slowing down in the proximity of food; the second approach modifies the basic algorithm in order to make the particles actually stop on the food source and remain there to eat. The results show that the changes convert the standard algorithm into one which produces qualitatively realistic behaviour for a simplified model act animals and their foraging environment. This work introduces a new way to look at the particle swarm algorithm, i.e. using it as a simulation tool in the biological field of behavioural ecology. To our knowledge, this is the first time particle swarm algorithms have been applied to problems in b...
Cecilia Di Chio, Riccardo Poli, Paolo Di Chio
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2006
Where ANTSW
Authors Cecilia Di Chio, Riccardo Poli, Paolo Di Chio
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