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
Link To Document :
بازگشت