Abstract

Using Gaussian Processes to Optimise Concession in Complex Negotiations against Unknown Opponents
Using Gaussian Processes to Optimise Concession in Complex Negotiations against Unknown Opponents
Colin R. Williams, Valentin Robu, Enrico H. Gerding, Nicholas R. Jennings
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.