A Shopping Negotiation Agent That Adapts to User Preferences

Authors:
Runhe Huang;Jianhua Ma;Qun Jin
Affiliations:
-;-;-
Venue:
AMT '01 Proceedings of the 6th International Computer Science Conference on Active Media Technology
Year:
2001

Citing 5
Cited 0

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Abstract

This paper describes a shopping negotiation agent that can adapt user preferences and automatically negotiate with its counter party on behalf of a user it represents. The agent is built on a basis of the proposed negotiation model, the enhanced extended Bazaar model, which is a sequence of decision making model of negotiation with exploiting common knowledge, public information, and game theory. Since different users can have different preferences, it is important for the agent to have adaptation to different user preferences. This can be achieved by acquiring user preferences, tracing user's behavior on Web and mapping the behavior to a set of the preference parameters, creating the negotiation model class, and generating an instance negotiation model object with new/updated preference parameters.