A Novel Strategy for Efficient Negotiation in Complex Environments

  • Siqi Chen
  • Gerhard Weiss
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7598)


A complex and challenging bilateral negotiation environment for rational autonomous agents is where agents negotiate multi-issue contracts in unknown application domains against unknown opponents under real-time constraints. In this paper we present a novel negotiation strategy called EMAR for this kind of environment which is based on a combination of Empirical Mode Decomposition (EMD) and Autoregressive Moving Average (ARMA). EMAR enables a negotiating agent to adjust its target utility and concession rate adaptively in real-time according to the behavior of its opponent. The experimental results show that this new strategy outperforms the best agents from the latest Automated Negotiation Agents (ANAC) Competition in a wide range of application domains.


Multiagent System Empirical Mode Decomposition Negotiation Strategy Minimum Utility Automate Negotiation 
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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© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Siqi Chen
    • 1
  • Gerhard Weiss
    • 1
  1. 1.Department of Knowledge EngineeringMaastricht UniversityMaastrichtThe Netherlands

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