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Publication Detail
Evolution of Force-Generating Equations for PSO using GP
  • Publication Type:
    Conference
  • Authors:
    Chio CD, Poli R, Langdon WB
  • Publication date:
    20/09/2005
  • Place of publication:
    University of Milan Bicocca, Italy
  • Published proceedings:
    AI*IA Workshop on Evolutionary Computation, Evoluzionistico GSICE05
  • Editors:
    Manzoni S,Palmonari M,Sartori F
  • ISBN-10:
    88-900910-0-2
  • Notes:
    keywords: genetic algorithms, genetic programming, XPS size: 10 pages notes: 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
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.
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