The University of Southampton
University of Southampton Institutional Repository

Accepting optimally in automated negotiation with incomplete information

Accepting optimally in automated negotiation with incomplete information
Accepting optimally in automated negotiation with incomplete information
When a negotiating agent is presented with an offer by its opponent, it is faced with a decision: it can accept the offer that is currently on the table, or it can reject it and continue the negotiation. Both options involve an inherent risk: continuing the negotiation carries the risk of forgoing a possibly optimal offer, whereas accepting runs the risk of missing out on an even better future offer. We approach the decision of whether to accept as a sequential decision problem, by modeling the bids received as a stochastic process. We argue that this is a natural choice in the context of a negotiation with incomplete information, where the future behavior of the opponent is uncertain. We determine the optimal acceptance policies for particular opponent classes and we present an approach to estimate the expected range of offers when the type of opponent is unknown. We apply our method against a wide range of opponents, and compare its performance with acceptance mechanisms of state-of-the-art negotiation strategies. The experiments show that the proposed approach is able to find the optimal time to accept, and improves upon widely used existing acceptance mechanisms.
acceptance strategy, negotiation, optimal stopping
978-1-4503-1993-5
715-722
Baarslag, Tim
a7c541d8-8141-467b-a08c-7a81cd69920e
Hindriks, Koen V.
04b551cd-49a6-49cf-9c83-e1a19317eb0d
Baarslag, Tim
a7c541d8-8141-467b-a08c-7a81cd69920e
Hindriks, Koen V.
04b551cd-49a6-49cf-9c83-e1a19317eb0d

Baarslag, Tim and Hindriks, Koen V. (2013) Accepting optimally in automated negotiation with incomplete information. AAMAS2013: 2013 International Conference on Autonomous Agents and Multi-agent Systems, Saint Paul, United States. 06 - 10 May 2013. pp. 715-722 .

Record type: Conference or Workshop Item (Paper)

Abstract

When a negotiating agent is presented with an offer by its opponent, it is faced with a decision: it can accept the offer that is currently on the table, or it can reject it and continue the negotiation. Both options involve an inherent risk: continuing the negotiation carries the risk of forgoing a possibly optimal offer, whereas accepting runs the risk of missing out on an even better future offer. We approach the decision of whether to accept as a sequential decision problem, by modeling the bids received as a stochastic process. We argue that this is a natural choice in the context of a negotiation with incomplete information, where the future behavior of the opponent is uncertain. We determine the optimal acceptance policies for particular opponent classes and we present an approach to estimate the expected range of offers when the type of opponent is unknown. We apply our method against a wide range of opponents, and compare its performance with acceptance mechanisms of state-of-the-art negotiation strategies. The experiments show that the proposed approach is able to find the optimal time to accept, and improves upon widely used existing acceptance mechanisms.

Text
Accepting Optimally in Automated Negotiation with Incomplete Information.pdf - Other
Download (766kB)

More information

Published date: May 2013
Venue - Dates: AAMAS2013: 2013 International Conference on Autonomous Agents and Multi-agent Systems, Saint Paul, United States, 2013-05-06 - 2013-05-10
Keywords: acceptance strategy, negotiation, optimal stopping
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 373623
URI: http://eprints.soton.ac.uk/id/eprint/373623
ISBN: 978-1-4503-1993-5
PURE UUID: a3b0f735-9ef9-4259-8fc5-952e8d881e42
ORCID for Tim Baarslag: ORCID iD orcid.org/0000-0002-1662-3910

Catalogue record

Date deposited: 27 Jan 2015 14:06
Last modified: 14 Mar 2024 18:55

Export record

Contributors

Author: Tim Baarslag ORCID iD
Author: Koen V. Hindriks

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.

×