Temporal difference learning and TD-Gammon
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
Computational Model for Online Agent Negotiation
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 1 - Volume 1
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
The design and evaluation of an intelligent sales agent for online persuasion and negotiation
Electronic Commerce Research and Applications
LEARNING DRIFTING NEGOTIATIONS
Applied Artificial Intelligence
The evaluation of intelligent agent performance - An example of B2C e-commerce negotiation
Computer Standards & Interfaces
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Online purchase from e-stores is getting popular as the prevalence of electronic commerce. At current stage, most e-stores resemble vending machines rather than real stores because they lack clerks to persuade prospects into buying products and to bargain with the customers for making a good deal. This research designs an easy-to-use and autonomous sales-agent to act as a virtual clerk in an e-store, and then investigates whether an e-store with this virtual clerk could increase customers' product evaluation and seller's surplus. This research starts with proposing a new approach to enable the intelligent sales-agent, named Isa, to dynamically adopt different persuasion and negotiation strategies according to different characteristics of human buyers. Additionally, the agent can learn to execute beneficial strategies by itself without seller's instructions. A field experiment was conducted to assess this agent. The experimental results reveal that Isa can autonomously persuade buyers into increasing their product evaluation and willingness to pay more money for product. Isa can also improve sellers' surplus and buyers' satisfaction with e-store.