Evolution of Force-Generating Equations for PSO using GP

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@InProceedings{DiChio:2005:gsice,

• author = "Cecilia {Di Chio} and Riccardo Poli and William B. Langdon",
• title = "Evolution of Force-Generating Equations for {PSO} using {GP}",
• booktitle = "AI*IA Workshop on Evolutionary Computation, Evoluzionistico GSICE05",
• year = "2005",
• editor = "Sara Manzoni and Matteo Palmonari and Fabio Sartori",
• address = "University of Milan Bicocca, Italy",
• month = "20 " # sep,
• keywords = "genetic algorithms, genetic programming, particle swarm optimisation, XPS",
• ISBN = "88-900910-0-2",
• URL = "http://www.cs.essex.ac.uk/staff/poli/papers/gsice2005.pdf",
• size = "10 pages",
• abstract = "We extend our previous research on evolving the physical forces which control particle swarms by considering additional ingredients, such as the velocity of the neighbourhood best and time, and different neighbourhood topologies, namely the global and local ones. We test the evolved extended PSOs (XPSOs) on various classes of benchmark problems.

  We show that evolutionary computation, and in particular genetic programming (GP), can automatically generate new PSO algorithms that outperform standard PSOs designed by people as well as some previously evolved ones.",

• notes = "http://www.ce.unipr.it/people/cagnoni/gsice2005/ http://www.ce.unipr.it/people/cagnoni/gsice2005/gsice-eng.pdf Workshop proceedings on CD-ROM only. Workshop held in-conjunction with the IX Congress of the Italian Association for Artificial Intelligence. In English.

  Winner of Best Paper Award",

}

Genetic Programming entries for Cecilia Di Chio Riccardo Poli William B Langdon

Citations