• DocumentCode
    2728759
  • Title

    Tree swarm optimization: an approach to PSO-based tree discovery

  • Author

    Veenhuis, Christian ; Köppen, Mario ; Kruger, Jörg ; Nickolay, Bertram

  • Author_Institution
    Fraunhofer IPK, Berlin, Germany
  • Volume
    2
  • fYear
    2005
  • fDate
    2-5 Sept. 2005
  • Firstpage
    1238
  • Abstract
    In recent years a swarm-based optimization methodology called particle swarm optimization (PSO) has developed. PSO is highly explorative and primarily used in function optimization. This paper proposes a swarm-based learning algorithm based on PSO which is able to discover trees in tree spaces. Particles are flying through a tree space forming flocks around peaks of a fitness function. Because it inherits the explorative property of PSO, it needs only few evaluations to find suitable trees.
  • Keywords
    learning (artificial intelligence); particle swarm optimisation; trees (mathematics); fitness function; function optimization; particle swarm optimization; swarm-based learning algorithm; tree discovery; tree spaces; tree swarm optimization; Ant colony optimization; Assembly; Birds; Classification tree analysis; Decision trees; Genetic programming; Machine learning; Machine learning algorithms; Optimization methods; Particle swarm optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2005. The 2005 IEEE Congress on
  • Print_ISBN
    0-7803-9363-5
  • Type

    conf

  • DOI
    10.1109/CEC.2005.1554832
  • Filename
    1554832