DocumentCode :
529330
Title :
Automatic program generation with genetic network programming using subroutines
Author :
Li, Bing ; Mabu, Shingo ; Hirasawa, Kotaro
Author_Institution :
Grad. Sch. of Inf., Production & Syst., Waseda Univ., Fukuoka, Japan
fYear :
2010
fDate :
18-21 Aug. 2010
Firstpage :
3089
Lastpage :
3094
Abstract :
Genetic Network Programming with Automatic Program Generation (GNP-APG) is an evolutionary algorithm to generate programs. Genotype-phenotype mapping technology is introduced in this algorithm to create legal programs. With the help of graph-based structures of Genetic Network Programming (GNP), GNP-APG can efficiently generate robust programs to cope with problems. In this paper, the extended algorithm of GNP-APG is proposed which can create a hierarchy program, in other words, a program which contains a main function and subroutines. The proposed method works like Automatic Defined Functions (ADFs) in Genetic Programming (GP). By using subroutines, a complex program can be decomposed to several simple programs which are obtained more easily. Moreover, these subroutines might be called many times, which results in reducing the size of the program significantly. In simulations, different tile-worlds between the training phase and testing phase are used for performance evaluations and the results shows that GNP-APG with subroutines (GNP-APGsr) could have better performances than GNP-APG.
Keywords :
automatic programming; genetic algorithms; performance evaluation; subroutines; automatic program generation; evolutionary algorithm; genetic network programming; genotype phenotype mapping technology; graph based structure; subroutine program; Algorithms; Economic indicators; Evolutionary computation; Genetics; Next generation networking; Programming; Tiles; Genetic Network Programming; Genetic Programming; Tile-world; program generation; subroutines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
SICE Annual Conference 2010, Proceedings of
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-7642-8
Type :
conf
Filename :
5602565
Link To Document :
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