DocumentCode
3237289
Title
Cooperative coevolutionary genetic algorithms to find optimal elimination orderings for Bayesian networks
Author
Dong, Xuchu ; Yu, Haihong ; Ouyang, Dantong ; Cai, Dianbo ; Ye, Yuxin ; Zhang, Yonggang
Author_Institution
Dept. of Comput. Sci. & Technol., Jilin Univ., Changchun, China
fYear
2010
fDate
23-26 Sept. 2010
Firstpage
1388
Lastpage
1394
Abstract
According to the characteristics of the optimal elimination ordering problem in Bayesian networks, a heuristic-based genetic algorithm, a cooperative coevolutionary genetic framework and five grouping schemes are proposed. Based on these works, six cooperative coevolutionary genetic algorithms are constructed. Numerical experiments show that these algorithms are more robust than other existing swarm intelligence methods when solving the elimination ordering problem.
Keywords
belief networks; genetic algorithms; Bayesian network; cooperative coevolutionary genetic algorithm; heuristic-based genetic algorithm; optimal elimination ordering; Bayesian methods; Genetics; Robustness; Bayesian networks; cooperative coevolution; elimination ordering; genetic algorithms; grouping scheme;
fLanguage
English
Publisher
ieee
Conference_Titel
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Conference_Location
Changsha
Print_ISBN
978-1-4244-6437-1
Type
conf
DOI
10.1109/BICTA.2010.5645605
Filename
5645605
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