DocumentCode
3591949
Title
A Multi-heuristic Cooperative Ant Colony System for Optimizing Elimination Ordering of Bayesian Networks
Author
Dong, Xuchu ; Ouyang, Dantong ; Ye, Yuxin ; Yu, Haihong ; Zhang, Yonggang
Author_Institution
Dept. of Comput. Sci. & Technol., Jilin Univ., Jilin, China
Volume
2
fYear
2010
Firstpage
75
Lastpage
78
Abstract
To solve the problem of searching for an optimal elimination ordering of Bayesian networks, a novel effective heuristic, MinSum Weight, and an ACS approach incorporated with multi-heuristic mechanism are proposed. The ACS approach named MHC-ACS utilizes a set of heuristics to direct the ants moving in the search space. The cooperation of multiple heuristics helps ants explore more regions. Moreover, the most appropriate heuristic will be identified and be reinforced with the evolution of the whole system. Experiments demonstrate that MHC-ACS has a better performance than other swarm intelligence methods.
Keywords
belief networks; optimisation; Bayesian networks; MinSum weight; multiheuristic cooperative ant colony system; multiheuristic mechanism; optimizing elimination ordering; swarm intelligence methods; Bayesian network; ant colony system; elimination ordering; heuristics; junction tree;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2010 IEEE/WIC/ACM International Conference on
Print_ISBN
978-1-4244-8482-9
Electronic_ISBN
978-0-7695-4191-4
Type
conf
DOI
10.1109/WI-IAT.2010.33
Filename
5616398
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