• DocumentCode
    3620293
  • Title

    Recombinative EMCMC algorithms

  • Author

    M.M. Drugan;D. Thierens

  • Author_Institution
    Dept. of Comput. Sci., Utrecht Univ., Netherlands
  • Volume
    3
  • fYear
    2005
  • fDate
    6/27/1905 12:00:00 AM
  • Firstpage
    2024
  • Abstract
    Evolutionary Markov chain Monte Carlo (EMCMC) is a class of algorithms obtained by merging Markov chain Monte Carlo algorithms with evolutionary computation methods. EMCMC integrates techniques from the EC framework (population, recombination and selection) into the MCMC framework to increase the performance of the standard MCMC algorithms. In this paper, we show how to use recombination operators in EMCMC and how to combine them with other existing MCMC techniques (e.g. mutation and selection). We illustrate these principles by means of an example.
  • Keywords
    "Monte Carlo methods","Computer science","Sampling methods","Probability distribution","Space exploration","Merging","Evolutionary computation","Genetic mutations","Convergence","Stochastic processes"
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2005. The 2005 IEEE Congress on
  • Print_ISBN
    0-7803-9363-5
  • Type

    conf

  • DOI
    10.1109/CEC.2005.1554944
  • Filename
    1554944