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Conference Paper: Computational method for agent-based E-commerce negotiations with adaptive negotiation behaviors

TitleComputational method for agent-based E-commerce negotiations with adaptive negotiation behaviors
Authors
KeywordsAgent
Case-based reasoning
E-commerce
Negotiation
Neural network
Issue Date2011
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/wps/find/journaldescription.cws_home/719435/description#description
Citation
The International Conference on Computational Science (ICCS 2011), Singapore, 1-3 June 2011. In Procedia Computer Science, 2011, v. 4, p. 1834-1843 How to Cite?
AbstractThis paper presents a computational method to organize agent-based E-commerce negotiations with adaptive negotiation behaviors aiming at enhancing the negotiation power and flexibility of software agents to alleviate human involvements in Ecommerce negotiations. Firstly, the computational expression of E-commerce negotiation, including negotiation issues and strategies, is specified to assist agents' computing functions. Then, an adaptive negotiation behavior configuration mechanism is proposed to tackle the negotiation dynamics through computation. In this three-staged mechanism, agents' negotiation behaviors are deployed by a case-based strategy assignment mechanism before the starting of negotiation; then along the on-going negotiation sequence, opponents' negotiation behaviors are tracked through Back-Propagation Neural Network (BP-NN) learning model to make strategy adjustment to confront the opponent. After the negotiation, opponents' concession functions are recorded and analysed using time series measure. Finally, the feasibility of the BP-NN learning model is verified through a set of tests. The computational negotiation method is exemplified using a two-issue buyer-seller negotiation case. The outcomes show that the adaptive negotiation behavior configuration mechanism can benefit an agent to win more in the E-commerce negotiation. © 2011 Published by Elsevier Ltd.
DescriptionThis journal vol. is proceedings of the International Conference on Computational Science, ICCS 2011
Persistent Identifierhttp://hdl.handle.net/10722/135891
ISSN
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWang, Gen_HK
dc.contributor.authorWong, TNen_HK
dc.contributor.authorYu, Cen_HK
dc.date.accessioned2011-07-27T01:50:07Z-
dc.date.available2011-07-27T01:50:07Z-
dc.date.issued2011en_HK
dc.identifier.citationThe International Conference on Computational Science (ICCS 2011), Singapore, 1-3 June 2011. In Procedia Computer Science, 2011, v. 4, p. 1834-1843en_US
dc.identifier.issn1877-0509en_HK
dc.identifier.urihttp://hdl.handle.net/10722/135891-
dc.descriptionThis journal vol. is proceedings of the International Conference on Computational Science, ICCS 2011en_US
dc.description.abstractThis paper presents a computational method to organize agent-based E-commerce negotiations with adaptive negotiation behaviors aiming at enhancing the negotiation power and flexibility of software agents to alleviate human involvements in Ecommerce negotiations. Firstly, the computational expression of E-commerce negotiation, including negotiation issues and strategies, is specified to assist agents' computing functions. Then, an adaptive negotiation behavior configuration mechanism is proposed to tackle the negotiation dynamics through computation. In this three-staged mechanism, agents' negotiation behaviors are deployed by a case-based strategy assignment mechanism before the starting of negotiation; then along the on-going negotiation sequence, opponents' negotiation behaviors are tracked through Back-Propagation Neural Network (BP-NN) learning model to make strategy adjustment to confront the opponent. After the negotiation, opponents' concession functions are recorded and analysed using time series measure. Finally, the feasibility of the BP-NN learning model is verified through a set of tests. The computational negotiation method is exemplified using a two-issue buyer-seller negotiation case. The outcomes show that the adaptive negotiation behavior configuration mechanism can benefit an agent to win more in the E-commerce negotiation. © 2011 Published by Elsevier Ltd.en_HK
dc.languageengen_US
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/wps/find/journaldescription.cws_home/719435/description#description-
dc.relation.ispartofProcedia Computer Scienceen_HK
dc.subjectAgenten_HK
dc.subjectCase-based reasoningen_HK
dc.subjectE-commerceen_HK
dc.subjectNegotiationen_HK
dc.subjectNeural networken_HK
dc.titleComputational method for agent-based E-commerce negotiations with adaptive negotiation behaviorsen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailWang, G: wanggong@hku.hken_HK
dc.identifier.emailWong, TN: tnwong@hku.hk-
dc.identifier.emailYu, C: cxyu@hku.hk-
dc.identifier.authorityWong, TN=rp00192en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.procs.2011.04.199en_HK
dc.identifier.scopuseid_2-s2.0-79958275687en_HK
dc.identifier.hkuros186780en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79958275687&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume4en_HK
dc.identifier.spage1834en_HK
dc.identifier.epage1843en_HK
dc.identifier.isiWOS:000299165200198-
dc.publisher.placeNetherlands-
dc.description.otherThe International Conference on Computational Science (ICCS 2011), Singapore, 1-3 June 2011. In Procedia Computer Science, 2011, v. 4, p. 1834-1843-
dc.identifier.scopusauthoridYu, C=41662510600en_HK
dc.identifier.scopusauthoridWong, TN=55301015400en_HK
dc.identifier.scopusauthoridWang, G=36618061900en_HK

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