Name
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. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11839088_58 | ANTS Workshop |
Keywords | Field | DocType |
grouping behaviour,standard algorithm,particle swarm algorithm,general requirement,behavioural ecology,continuous equation,biological problem,foraging problem,classical optimisation problem,animal foraging behaviour,group-foraging problem,continuity equation,particle swarm | Mathematical optimization,Standard algorithms,Evolutionary algorithm,Computer science,Swarm intelligence,Artificial intelligence,Animal Foraging,Particle swarm algorithm,Equations of motion,Artificial neural network,Foraging,Distributed computing | Conference |
Volume | ISSN | ISBN |
4150 | 0302-9743 | 3-540-38482-0 |
Citations | PageRank | References |
2 | 0.82 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cecilia Di Chio | 1 | 251 | 21.24 |
| Riccardo Poli | 2 | 2589 | 308.79 |
| Paolo Di Chio | 3 | 22 | 5.36 |