Authors:
Sandhya Beldona
and
Costas Tsatsoulis
Affiliation:
Information and Telecommunication Technology Center, The University of Kansas, United States
Keyword(s):
Autonomous agents, Learning, Distributed, Trust, Reputation, Ecommerce, Electronic Markets.
Related
Ontology
Subjects/Areas/Topics:
Autonomous Agents
;
Informatics in Control, Automation and Robotics
;
Robotics and Automation
Abstract:
Previous research in the area of buyer agent strategies for choosing seller agents in ecommerce markets has focused on frequent purchases. In this paper we present a reputation based buyer agent strategy for choosing seller agent in a decentralized, open, uncertain, dynamic, and untrusted B2C ecommerce market for frequent and infrequent purchases. The buyer agent models the reputation of the seller agent after having purchased goods from it. The buyer agent has certain expectations of quality and the reputation of a seller agent reflects the seller agent’s ability to provide the product at the buyer agent’s expectation level, and its price compared to its competitors in the market. The reputation of the seller agents and the price quoted by the seller agents are used to choose a seller agent to transact with. We compare the performance of our model with other strategies that have been proposed for this kind of market. Our results indicate that a buyer agent using our model experience
s a slight improvement for frequent purchases and significant improvement for infrequent purchases.
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