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Conference Paper: Agent swarm regression network ASRN

TitleAgent swarm regression network ASRN
Authors
Chow, C-KTsui, H-T
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?
DOI: http://dx.doi.org/10.1109/ICSMC.2004.1401087
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
0-7803-8566-7
ISSN
1062-922X
2020 SCImago Journal Rankings: 0.168

 

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.rights©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
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-
dc.identifier.issnl1062-922X-

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