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
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Williams, C.R., Robu, V., Gerding, E.H., Jennings, N.R. (2012). IAMhaggler: A Negotiation Agent for Complex Environments. In: Ito, T., Zhang, M., Robu, V., Fatima, S., Matsuo, T. (eds) New Trends in Agent-Based Complex Automated Negotiations. Studies in Computational Intelligence, vol 383. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24696-8_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24695-1
Online ISBN: 978-3-642-24696-8