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Conference Paper: Agent swarm regression network ASRN

TitleAgent swarm regression network ASRN
Authors
KeywordsMulti-Agent System
RBF neural nehvork
Regression
Issue Date2004
PublisherInstitute of Electrical and Electronics Engineers. The Journal's website is located at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9622
Citation
The 2004 IEEE International Conference on Systems, Man and Cybernetics (SMC 2004), Hague, The Netherlands, 10-13 October 2004. In IEEE International Conference on Systems, Man, and Cybernetics. Conference Proceedings, 2004, v. 6, p. 5609-5614 How to Cite?
AbstractA multi-agent system (MAS), with independent software agents interacting with each other to achieve common goals will complete concurrent distributed tasks under autonomous control. In this paper, novel RBF Regression Network - "Agent Swarm Regression Network ASRN" is proposed and will be trained by a MAS. Each neuron of the ASRN is considered as an agent, which consists of per-deflned simple agent behavior set. After a sufficient number of iterations, the weights of neurons can be determined. Two sets of experiment will be examined to observe the effectiveness of the proposed method. © 2004 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/196650
ISBN
ISSN

 

DC FieldValueLanguage
dc.contributor.authorChow, C-K-
dc.contributor.authorTsui, H-T-
dc.date.accessioned2014-04-24T02:10:31Z-
dc.date.available2014-04-24T02:10:31Z-
dc.date.issued2004-
dc.identifier.citationThe 2004 IEEE International Conference on Systems, Man and Cybernetics (SMC 2004), Hague, The Netherlands, 10-13 October 2004. In IEEE International Conference on Systems, Man, and Cybernetics. Conference Proceedings, 2004, v. 6, p. 5609-5614-
dc.identifier.isbn0-7803-8566-7-
dc.identifier.issn1062-922X-
dc.identifier.urihttp://hdl.handle.net/10722/196650-
dc.description.abstractA multi-agent system (MAS), with independent software agents interacting with each other to achieve common goals will complete concurrent distributed tasks under autonomous control. In this paper, novel RBF Regression Network - "Agent Swarm Regression Network ASRN" is proposed and will be trained by a MAS. Each neuron of the ASRN is considered as an agent, which consists of per-deflned simple agent behavior set. After a sufficient number of iterations, the weights of neurons can be determined. Two sets of experiment will be examined to observe the effectiveness of the proposed method. © 2004 IEEE.-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers. The Journal's website is located at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9622-
dc.relation.ispartofIEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsIEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings. Copyright © Institute of Electrical and Electronics Engineers.-
dc.subjectMulti-Agent System-
dc.subjectRBF neural nehvork-
dc.subjectRegression-
dc.titleAgent swarm regression network ASRN-
dc.typeConference_Paper-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ICSMC.2004.1401087-
dc.identifier.scopuseid_2-s2.0-15744373008-
dc.identifier.volume6-
dc.identifier.spage5609-
dc.identifier.epage5614-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 160603 amended-

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