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

Louta, M; Roussaki, I; Pechlivanos, L

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	https://dspace.lib.ntua.gr/xmlui/handle/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