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
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