Multi-agent E-commerce System Research Articles

Development of a Fuzzy-based Multi-agent System for E-commerce Settings

In this paper we present our experience in developing a fuzzy-logic based multi-agent e-commerce system capable of achieving a mutually beneficial deal for the seller and buyer using a negotiation process. We use fuzzy logic to assist users to express their preferences about a product in fuzzy terms such as low, medium and high. Our system evaluates offers based on a fuzzy utility function and feeds utility scores to a fuzzy inference system which then computes its next counter offer. Our paper presents issues involved in the development of a multi-agent system for e-commerce settings using the JADE platform - a modern agent development environment. In this paper our focus is on implementing agents of different types/roles engaged in activities usually encountered with buying and selling in an e-commerce environment. Our concluding remarks and future research are presented.

A familiarity-based trust model for effective selection of sellers in multiagent e-commerce systems

In electronic marketplaces, trust is modeled, for instance, in order to allow buying agents to make effective selection of selling agents. Familiarity is often considered to be an important factor in determining the level of trust. In previous research, familiarity between two agents has been simply assumed to be the similarity between them. We propose an improved familiarity measurement based on the exploration of factors that affect a human’s feelings of familiarity. We also carry out experiments to show that the trust model with our improved familiarity measurement is more effective and more stable.