Estimation of the buyer's contract space incorporating learning from experience techniques to the seller's rationale in E-commerce context

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dc.contributor.author Louta, M en
dc.contributor.author Roussaki, I en
dc.contributor.author Pechlivanos, L en
dc.date.accessioned 2014-03-01T02:43:17Z
dc.date.available 2014-03-01T02:43:17Z
dc.date.issued 2005 en
dc.identifier.uri http://hdl.handle.net/123456789/31326
dc.subject Autonomous Agent en
dc.subject E Commerce en
dc.subject Empirical Evaluation en
dc.subject Learning From Experience en
dc.subject Mobile Agent en
dc.subject.other Decision theory en
dc.subject.other Electronic commerce en
dc.subject.other Intelligent agents en
dc.subject.other Knowledge acquisition en
dc.subject.other Mathematical models en
dc.subject.other Online systems en
dc.subject.other Software agents en
dc.subject.other Mobile agents en
dc.subject.other Negotiation model en
dc.subject.other Contracts en
dc.title Estimation of the buyer's contract space incorporating learning from experience techniques to the seller's rationale in E-commerce context en
heal.type conferenceItem en
heal.identifier.primary 10.1109/IAT.2005.70 en
heal.identifier.secondary http://dx.doi.org/10.1109/IAT.2005.70 en
heal.identifier.secondary 1565617 en
heal.publicationDate 2005 en
heal.abstract Various state-of-the-art technologies are necessary to enhance the efficiency and increase the interest for e-commerce transactions. Mobile agents are one of the means that may enhance the intelligence and improve the effectiveness of systems in the e-marketplace. This paper aims to present the basic elements of the designed dynamic multilateral negotiation model and strategies that do not require a complicated rationale on behalf of the buyer agents. It focuses on the enhancement of the Seller's reasoning component by incorporating to the designed negotiation strategies a novel mechanism for the estimation of the mutually acceptable contract region by exploiting relative market data combined with knowledge acquired from previous experience. This technique is used to extend the functionality of autonomous agents, so that they reach to an agreement faster aiming to maximise their owner's utility. The framework considers both contract and decision issues, is based on real market conditions, and has been empirically evaluated. © 2005 IEEE. en
heal.journalName Proceedings - 2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT'05 en
dc.identifier.doi 10.1109/IAT.2005.70 en
dc.identifier.volume 2005 en
dc.identifier.spage 646 en
dc.identifier.epage 652 en

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