DocumentCode
445469
Title
A note on the population based incremental learning with infinite population size
Author
Rastegar, R. ; Meybodi, M.R.
Author_Institution
Comput. Eng. & IT Dept., Amirkabir Univ. of Technol., Tehran
Volume
1
fYear
2005
fDate
5-5 Sept. 2005
Firstpage
198
Abstract
In this paper, we study the dynamical properties of the population based incremental learning (PBIL) algorithm when it uses truncation, proportional, and Boltzmann selection schemas. The results show that if the population size tends to infinity, with any learning rate, the local optima of the function to be optimized are asymptotically stable fixed points of the PBIL
Keywords
distributed algorithms; genetic algorithms; learning (artificial intelligence); search problems; Boltzmann selection schemas; distribution algorithms; genetic algorithms; infinite population size; population based incremental learning algorithm; Algorithm design and analysis; Biological cells; Buildings; Clustering algorithms; Electronic design automation and methodology; Genetic algorithms; Genetic mutations; H infinity control; Learning automata; Mutual information;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Conference_Location
Edinburgh, Scotland
Print_ISBN
0-7803-9363-5
Type
conf
DOI
10.1109/CEC.2005.1554685
Filename
1554685
Link To Document