Abstract
A wide range of algorithms have been developed for various types of automated negotiation. In developing such algorithms the main focus has been on their efficiency and their effectiveness. However, this is only part of the picture. Agents typically negotiate on behalf of their owner and for this to be effective, the agent must be able to adequately represent their owners’ preferences. However, the process by which such knowledge is acquired is typically left unspecified. To remove this shortcoming, we present a case study indicating how the knowledge for a particular negotiation algorithm can be acquired. Specifically, we devise new knowledge acquisition techniques for obtaining information about a user’s tradeoffs between various negotiation issues and develop knowledge acquisition tools to support this endeavour.
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Luo, X., Jennings, N.R., Shadbolt, N. (2004). Acquiring Tradeoff Preferences for Automated Negotiations: A Case Study. In: Faratin, P., Parkes, D.C., RodrĂguez-Aguilar, J.A., Walsh, W.E. (eds) Agent-Mediated Electronic Commerce V. Designing Mechanisms and Systems. AMEC 2003. Lecture Notes in Computer Science(), vol 3048. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25947-3_3
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DOI: https://doi.org/10.1007/978-3-540-25947-3_3
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