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<p>The authors propose a multiagent framework, called the OLDyB system, to facilitate an online automated bargaining process for electronic trading. They designed a dynamic price-issuing agent based on the utility theory to offer prices and determine when to close a deal. A pattern-generalization agent logs and then processes the bargaining steps to generalize bargaining patterns. During the bargaining process, the pattern-matching agent tries to match the bargaining steps with the discovered bargaining patterns to return a price to the buyer using the pattern-matching algorithm. When failing to match patterns, the matching agent will invoke the dynamic price-issuing agent to offer prices. The authors conducted a field experiment to evaluate the proposed framework in different sellers' risk perspectives and compared the performance with existing bargaining methods. The results show that the proposed methods obtain encouraging performance. This research initiates the efforts on developing data mining algorithms to support the price bargaining process for electronic commerce.</p>
Keywords: automated bargaining, dynamic price issuing, electronic commerce, multiagent system, utility.

F. Lin and K. Chang, "A Multiagent Framework for Automated Online Bargaining," in IEEE Intelligent Systems, vol. 16, no. , pp. 41-47, 2001.
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