The University of Southampton
University of Southampton Institutional Repository

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

Record type: Conference or Workshop Item (Paper)

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.

PDF ijcai11.pdf - Accepted Manuscript
Download (333kB)
PDF Using Gaussian Processes to Optimise Concession in Complex Negotiations against Unknown Opponents - Slides.pdf - Other
Download (1MB)
PDF Using Gaussian Processes to Optimise Concession in Complex Negotiations against Unknown Opponents - Poster.pdf - Other
Download (423kB)

Citation

Williams, Colin R., Robu, Valentin, Gerding, Enrico H. and Jennings, Nicholas R. (2011) Using Gaussian Processes to Optimise Concession in Complex Negotiations against Unknown Opponents At Proceedings of the 22nd International Joint Conference on Artificial Intelligence, Spain. 16 - 22 Jul 2011. 8 pp, pp. 432-438. (doi:10.5591/978-1-57735-516-8/IJCAI11-080).

More information

Submitted date: 26 January 2011
Published date: 2011
Additional Information: A video of the presentation is available at http://ijcai-11.iiia.csic.es/video/55
Venue - Dates: Proceedings of the 22nd International Joint Conference on Artificial Intelligence, Spain, 2011-07-16 - 2011-07-22
Keywords: Automated Negotiation, Multi-issue Negotiation
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 271965
URI: http://eprints.soton.ac.uk/id/eprint/271965
ISBN: 978-1-57735-512-0
PURE UUID: b3341638-fc75-40b1-9682-0e212cd3e161

Catalogue record

Date deposited: 31 Mar 2011 13:16
Last modified: 18 Jul 2017 06:36

Export record

Altmetrics

Contributors

Author: Colin R. Williams
Author: Valentin Robu
Author: Enrico H. Gerding
Author: Nicholas R. Jennings

University divisions


Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×