Cooperative vs. Competitive Multi-Agent Negotiations in Retail Electronic Commerce
CIA '98 Proceedings of the Second International Workshop on Cooperative Information Agents II, Learning, Mobility and Electronic Commerce for Information Discovery on the Internet
VEMA: Multi-Agent System for Electronic Commerce on Internet
HCI International '97 Proceedings of the Seventh International Conference on Human-Computer Interaction-Volume 1 - Volume I
Information and interaction in marketspace: towards an open agent-based market infrastructure
WOEC'96 Proceedings of the 2nd conference on Proceedings of the Second USENIX Workshop on Electronic Commerce - Volume 2
A framework for designing policies for networked systems with uncertainty
Decision Support Systems
Multi-Agent Negotiation in B2C E-Commerce Based on Data Mining Methods
International Journal of Intelligent Information Technologies
Multi-Agent Negotiation Paradigm for Agent Selection in B2C E-Commerce
International Journal of Agent Technologies and Systems
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Despite the rapid emergence of Internet-based electronic transactions, many users are still unfamiliar with the system and find it difficulty buying and selling products in the cyber marketplace. The agent-based virtual marketplace system, where agents take care of the transactions for individual users, has been suggested to solve this problem. Many of the models proposed for the system can be largely divided into two types. The first type is direct transaction between sellers and buyers, and the second is agent-based transaction. However, the deals between buyers and sellers are not made efficiently or fairly for both sides. To improve such conditions, this paper suggests a broker-based synchronous transaction algorithm that would guarantee a more fair and efficient transaction deal for both sellers and buyers. This algorithm, implemented by Visual C++, showed better performance in every aspect in the experiment for comparison with the current two model types. The number of transactions increased by 21% and the prices were adjusted up to 280% more efficiently in some transaction cases.