A learning process using svms for multi-agents decision classification

Xiao, Y; Deng, F; Liu, B; Liu, S; Luo, D; Liang, G

A learning process using svms for multi-agents decision classification

Xiao, Y Deng, F Liu, B Liu, S Luo, D Liang, G

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2008, 2008, pp. 583 - 586
Issue Date:: 2008-12-01

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Field	Value	Language
dc.contributor.author	Xiao, Y	en_US
dc.contributor.author	Deng, F	en_US
dc.contributor.author	Liu, B	en_US
dc.contributor.author	Liu, S	en_US
dc.contributor.author	Luo, D	en_US
dc.contributor.author	Liang, G https://orcid.org/0000-0002-6843-7431	en_US
dc.date.issued	2008-12-01	en_US
dc.identifier.citation	Proceedings - 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2008, 2008, pp. 583 - 586	en_US
dc.identifier.isbn	9780769534961	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16310
dc.description.abstract	In order to resolve decision classification problem in multiple agents system, this paper first introduces the architecture of multiple agents system. It then proposes a support vector machines based assessment approach, which has the ability to learn the rules form previous assessment results from domain experts. Finally, the experiment are conducted on the artificially dataset to illustrate how the proposed works, and the results show the proposed method has effective learning ability for decision classification problems. © 2008 IEEE.	en_US
dc.relation.ispartof	Proceedings - 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2008	en_US
dc.relation.isbasedon	10.1109/WIIAT.2008.430	en_US
dc.title	A learning process using svms for multi-agents decision classification	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Sydney, Australia	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

In order to resolve decision classification problem in multiple agents system, this paper first introduces the architecture of multiple agents system. It then proposes a support vector machines based assessment approach, which has the ability to learn the rules form previous assessment results from domain experts. Finally, the experiment are conducted on the artificially dataset to illustrate how the proposed works, and the results show the proposed method has effective learning ability for decision classification problems. © 2008 IEEE.

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http://hdl.handle.net/10453/16310