Enabling Negotiating Agents to Explore Very Large Outcome Spaces

Conference Paper (2022)
Author(s)

Thimjo Koca (Universiteit van Amsterdam)

Tim Baarslag (Universiteit Utrecht, Centrum Wiskunde & Informatica (CWI))

C.M. Jonker (Universiteit Leiden, TU Delft - Interactive Intelligence)

Research Group
Interactive Intelligence
Copyright
© 2022 Thimjo Koca, Tim Baarslag, C.M. Jonker
DOI related publication
https://doi.org/0.1007/978-3-031-20179-0_4
More Info
expand_more
Publication Year
2022
Language
English
Copyright
© 2022 Thimjo Koca, Tim Baarslag, C.M. Jonker
Research Group
Interactive Intelligence
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. @en
Pages (from-to)
67-83
ISBN (print)
9783031201783
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

This work presents BIDS (Bidding using Diversified Search), an algorithm that can be used by negotiating agents to search very large outcome spaces. BIDS provides a balance between being rapid, accurate, diverse, and scalable search, allowing agents to search spaces with as many as 10
250 possible outcomes on very run-of-the-mill hardware. We show that our algorithm can be used to respond to the three most common search queries employed by 87% of all agents from the Automated Negotiating Agents Competition. Furthermore, we validate one of our techniques by integrating it into negotiation platform GeniusWeb, to enable existing state-of-the-art agents (and future agents) to scale their use to very large outcome spaces.

Files

978_3_031_20179_0_4.pdf
(pdf | 0 Mb)
- Embargo expired in 10-04-2023
License info not available