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
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