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Using Gaussian Processes to Optimise Concession in Complex Negotiations against Unknown Opponents

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Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 432-437.

https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-080

Abstract

In multi-issue automated negotiation against unknown opponents, a key part of effective negotiation is the choice of concession strategy. In this paper, we develop a principled concession strategy, based on Gaussian processes predicting the opponent's future behaviour. We then use this to set the agent's concession rate dynamically during a single negotiation session. We analyse the performance of our strategy and show that it outperforms the state-of-the-art negotiating agents from the 2010 Automated Negotiating Agents Competition, in both a tournament setting and in self-play, across a variety of negotiation domains.

Colin R. Williams, Valentin Robu, Enrico H. Gerding, and Nicholas R. Jennings. 2011. Using Gaussian Processes to Optimise Concession in Complex Negotiations against Unknown Opponents. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11. IJCAI, 432–437. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-080
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