Model of game agent for auction-based negotiation

  • Authors:

  • Jun Hu;Chun Guan

  • Affiliations:

  • Department of Computer Science and Engineering, Nanchang University, Nanchang, China;Department of Computer Science and Engineering, Nanchang University, Nanchang, China

  • Venue:
  • CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
  • Year:
  • 2005

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Abstract

Some actual multi-agent automated negotiation systems using auction mechanism in e-commerce are inefficient, as buyer negotiation agents are lack of enough rationality and uneasy to determine appropriate bid price automatically according to different circumstance. In order to improve the auction-based negotiation efficiency of multi-agent system in e-commerce, this paper proposes a model of game agent for auction-based negotiation and a bid negotiation algorithm based on game theory, which provide a new effective way to establish buyer game agent for making buyer agent determine price more accurately and bid more rationally. As buyer agents bid in a more rational way, auction agents and buyer agents can finish negotiation more efficiently.