DocumentCode
2660182
Title
An adaptive multi-heuristic ant colony system for finding optimal elimination orderings in Bayesian networks
Author
Dong, Xuchu ; Zhang, Yonggang ; Cai, Dianbo ; Yu, Haihong ; Ye, Yuxin
Author_Institution
Dept. of Comput. Sci. & Technol., Jilin Univ., Changchun, China
fYear
2010
fDate
8-10 Sept. 2010
Firstpage
386
Lastpage
390
Abstract
To find an optimal elimination ordering for Bayesian networks, a multi-heuristic-based ant colony system named MHC-HS-ACS is proposed. MHC-HS-ACS uses a set of heuristics to guide the ants to search solutions. The heuristic set can evolve with the searching procedure in an adaptive way. MHC-HS-ACS also utilizes a heuristic-based local search to accelerate its convergence. Computational experiments show that MHC-HS-ACS can find very high quality solutions.
Keywords
belief networks; heuristic programming; optimisation; Bayesian networks; adaptive multiheuristic ant colony system; heuristic-based local search; optimal elimination orderings; Bayesian methods; Conferences; Electrical engineering; Ethics; IEEE catalog; Inference algorithms; Junctions; Bayesian network; ant colony system; elimination ordering; heuristics; local search;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical Engineering Computing Science and Automatic Control (CCE), 2010 7th International Conference on
Conference_Location
Tuxtla Gutierrez
Print_ISBN
978-1-4244-7312-0
Type
conf
DOI
10.1109/ICEEE.2010.5608653
Filename
5608653
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