Temporal difference learning and TD-Gammon
Communications of the ACM
Do electronic marketplaces lower the price of goods?
Communications of the ACM
Bayesian learning in negotiation
International Journal of Human-Computer Studies - Evolution and learning in multiagent systems
Reaching agreements through argumentation: a logical model and implementation
Artificial Intelligence
Introduction to Multiagent Systems
Introduction to Multiagent Systems
A Multiagent Framework for Automated Online Bargaining
IEEE Intelligent Systems
Learning to Predict by the Methods of Temporal Differences
Machine Learning
Negotiated Collusion: Modeling Social Language and its Relationship Effects in Intelligent Agents
User Modeling and User-Adapted Interaction
Designing intelligent sales-agent for online selling
ICEC '05 Proceedings of the 7th international conference on Electronic commerce
A machine-learning approach to automated negotiation and prospects for electronic commerce
Journal of Management Information Systems - Special issue: Information technology and its organizational impact
Agent-mediated electronic commerce: an MIT media laboratory perspective
International Journal of Electronic Commerce - Special issue: Intelligent agents for electronic commerce
Effect of bargaining in electronic commerce
International Journal of Electronic Commerce - Special issue: Intelligent agents for electronic commerce
International Journal of Electronic Commerce
Expert Systems with Applications: An International Journal
The evaluation of intelligent agent performance - An example of B2C e-commerce negotiation
Computer Standards & Interfaces
Efficient communication architecture for the C2C agent
Computer Standards & Interfaces
A utility concession curve data fitting model for quantitative analysis of negotiation styles
Expert Systems with Applications: An International Journal
Hi-index | 0.00 |
Online purchases from e-stores are getting popular among Internet users. Although many e-commerce activities, such as auctions, bargaining, and recommendation services are available, most e-stores lack clerk-like mechanisms to persuade potential buyers into buying products and to bargain with them for making a good deal. The objectives of this research are to design a lab prototype of a sales agent with persuasion and negotiation capabilities and to evaluate its effectiveness as a virtual clerk in an e-store. The prototypical intelligent sales agent (ISA) is equipped with reinforcement learning capabilities and an abstract argument framework. We conduct both laboratory and Internet experiments to assess ISA's performance. The experimental results reveal that an e-store embedded within such a sales agent can improve a seller's surplus and increase a buyer's product valuation, willingness-to-pay, and satisfaction with the e-store.