• DocumentCode
    2831955
  • Title

    A Convergence Proof for the Population Based Incremental Learning Algorithm

  • Author

    Rastegar, R. ; Hariri, A. ; Mazoochi, M.

  • Author_Institution
    Iran Telecommunication Research Center
  • fYear
    2005
  • fDate
    14-16 Nov. 2005
  • Firstpage
    387
  • Lastpage
    391
  • Abstract
    Here we propose a convergence proof for the population based incremental learning (PBIL). In our approach, first, we model the PBIL by the Markov process and approximate its behavior using Ordinary Differential Equation (ODE). Then we prove that the corresponding ODE doesn’t have any stable stationary points in [0,1]n, n is the number of variables, except the local maxima of the function to be optimized. Finally we show that this ODE and consequently the PBIL converge to one of these stable attractors.
  • Keywords
    Bayesian methods; Clustering algorithms; Convergence; Differential equations; Electronic design automation and methodology; Genetic algorithms; Learning automata; Markov processes; Mutual information; Space stations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 2005. ICTAI 05. 17th IEEE International Conference on
  • ISSN
    1082-3409
  • Print_ISBN
    0-7695-2488-5
  • Type

    conf

  • DOI
    10.1109/ICTAI.2005.6
  • Filename
    1562966