IAMhaggler: A Negotiation Agent for Complex Environments

Part of the Studies in Computational Intelligence book series (SCI, volume 383)


We describe the strategy used by our agent, IAMhaggler, which finished in third place in the 2010 Automated Negotiating Agent Competition. It uses a concession strategy to determine the utility level at which to make offers. This concession strategy uses a principled approach which considers the offers made by the opponent. It then uses a Pareto-search algorithm combined with Bayesian learning in order to generate a multi-issue offer with a specific utility as given by its concession strategy.


Utility Level Negotiation Strategy Bayesian Learning Automate Negotiation Negotiation Agent 
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 2012

Authors and Affiliations

  1. 1.School of Electronics and Computer ScienceUniversity of SouthamptonSouthamptonUK

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