Enabling Negotiating Agents to Explore Very Large Outcome Spaces

Thimjo Koça; Catholijn M. Jonker; Tim Baarslag

doi:10.1007/978-3-031-20179-0_4

Enabling Negotiating Agents to Explore Very Large Outcome Spaces

Thimjo Koça^*
, Catholijn M. Jonker
, Tim Baarslag

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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.

Original language	English
Title of host publication	Autonomous Agents and Multiagent Systems. Best and Visionary Papers
Subtitle of host publication	AAMAS 2022 Workshops, Virtual Event, May 9–13, 2022, Revised Selected Papers
Editors	Francisco S. Melo, Fei Fang
Place of Publication	Cham
Publisher	Springer
Pages	67-83
Number of pages	17
Edition	1
ISBN (Electronic)	978-3-031-20179-0
ISBN (Print)	978-3-031-20178-3
DOIs	https://doi.org/10.1007/978-3-031-20179-0_4
Publication status	Published - 6 Nov 2022

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	13441
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Bibliographical note

Funding Information:
Acknowledgements. The research reported in this article is part of Vidi research project VI.Vidi.203.044, financed by the Dutch Research Council (NWO).

Publisher Copyright:
© 2022, Springer Nature Switzerland AG.

Keywords

Automated negotiation
Very large negotiation domain
Search

Access to Document

10.1007/978-3-031-20179-0_4

978-3-031-20179-0_4Final published version, 637 KBLicence: Taverne

Cite this

Koça, T., Jonker, C. M., & Baarslag, T. (2022). Enabling Negotiating Agents to Explore Very Large Outcome Spaces. In F. S. Melo, & F. Fang (Eds.), Autonomous Agents and Multiagent Systems. Best and Visionary Papers: AAMAS 2022 Workshops, Virtual Event, May 9–13, 2022, Revised Selected Papers (1 ed., pp. 67-83). (Lecture Notes in Computer Science; Vol. 13441 ). Springer. https://doi.org/10.1007/978-3-031-20179-0_4

Koça, Thimjo ; Jonker, Catholijn M. ; Baarslag, Tim. / Enabling Negotiating Agents to Explore Very Large Outcome Spaces. Autonomous Agents and Multiagent Systems. Best and Visionary Papers: AAMAS 2022 Workshops, Virtual Event, May 9–13, 2022, Revised Selected Papers. editor / Francisco S. Melo ; Fei Fang. 1. ed. Cham : Springer, 2022. pp. 67-83 (Lecture Notes in Computer Science).

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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.",

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Koça, T, Jonker, CM & Baarslag, T 2022, Enabling Negotiating Agents to Explore Very Large Outcome Spaces. in FS Melo & F Fang (eds), Autonomous Agents and Multiagent Systems. Best and Visionary Papers: AAMAS 2022 Workshops, Virtual Event, May 9–13, 2022, Revised Selected Papers. 1 edn, Lecture Notes in Computer Science, vol. 13441 , Springer, Cham, pp. 67-83. https://doi.org/10.1007/978-3-031-20179-0_4

Enabling Negotiating Agents to Explore Very Large Outcome Spaces. / Koça, Thimjo; Jonker, Catholijn M.; Baarslag, Tim.
Autonomous Agents and Multiagent Systems. Best and Visionary Papers: AAMAS 2022 Workshops, Virtual Event, May 9–13, 2022, Revised Selected Papers. ed. / Francisco S. Melo; Fei Fang. 1. ed. Cham: Springer, 2022. p. 67-83 (Lecture Notes in Computer Science; Vol. 13441 ).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Koça T, Jonker CM, Baarslag T. Enabling Negotiating Agents to Explore Very Large Outcome Spaces. In Melo FS, Fang F, editors, Autonomous Agents and Multiagent Systems. Best and Visionary Papers: AAMAS 2022 Workshops, Virtual Event, May 9–13, 2022, Revised Selected Papers. 1 ed. Cham: Springer. 2022. p. 67-83. (Lecture Notes in Computer Science). doi: 10.1007/978-3-031-20179-0_4