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A Bayes Net Approach to Argumentation Based Negotiation

  • Sabyasachi Saha
  • Sandip Sen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3366)

Abstract

Negotiation is one of the most fundamental and effective mechanism for resolving conflicts between self-interested agents and producing mutually acceptable compromises. Most existing research in negotiation presumes a fixed negotiation context which cannot be changed during the process of negotiation and that the agents have complete and correct knowledge about all aspects of the issues being negotiated. In practice, the issues being negotiated may change and the agents may have incorrect beliefs of relevant issues updated during the negotiation process. Argumentation-based negotiation approaches have therefore been proposed to capture such realistic negotiation contexts. Here we present a novel Bayesian network based argumentation and decision making framework that allows agents to utilize models of the other agents. The agents will generate effective arguments to influence the other agent’s belief and produce more profit.

Keywords

Bayesian Network Multiagent System User Agent Travel Agent Decision Mechanism 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Sabyasachi Saha
    • 1
  • Sandip Sen
    • 1
  1. 1.Department of Mathematical & Computer SciencesUniversity of TulsaTulsaUSA

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