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
Link To Document :
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