DocumentCode
2218201
Title
Variable Size Genetic Network Programming with Binomial Distribution
Author
Li, Bing ; Li, Xianneng ; Mabu, Shingo ; Hirasawa, Kotaro
Author_Institution
Grad. Sch. of Inf., Waseda Univ., Kitakyushu, Japan
fYear
2011
fDate
5-8 June 2011
Firstpage
973
Lastpage
980
Abstract
This paper proposes a different type of Genetic Network Programming (GNP) Variable Size Genetic Network Programming (GNPvs) with Binomial Distribution. In contrast to the individuals with fixed size in Standard GNP, GNPvs will change the size of the individuals and obtain the optimal size of them during evolution. The proposed method defines a new type of crossover to implement the new feature of GNP. The new crossover will select the number of nodes to move from each parent GNP to another parent GNP. The probability of selecting the number of nodes to move satisfies the binomial probability distribution. The proposed method can keep the effectiveness of crossover and improve the performance of GNP. In order to verify the performance of the proposed method, a well-known benchmark problem Tile-world is used in the simulations. The simulation results show the effectiveness of the proposed method.
Keywords
algorithm theory; binomial distribution; genetic algorithms; binomial probability distribution; simulation; tile-world; variable size genetic network programming; Biological cells; Economic indicators; Genetic algorithms; Genetics; Probability distribution; Programming; Tiles; Binomial probability distribution; Crossover; Genetic Network Programming; Tile-world; Variable size;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2011 IEEE Congress on
Conference_Location
New Orleans, LA
ISSN
Pending
Print_ISBN
978-1-4244-7834-7
Type
conf
DOI
10.1109/CEC.2011.5949723
Filename
5949723
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