Enabling Negotiating Agents to Explore Very Large Outcome Spaces

Publication date

2022-11-06

Authors

Koça, Thimjo
Jonker, Catholijn M.
Baarslag, TimORCID 0000-0002-1662-3910ISNI 0000000419526790

Editors

Melo, Francisco S.
Fang, Fei

Advisors

Supervisors

Document Type

Part of book
Open Access logo

License

taverne

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.

Keywords

Automated negotiation, Very large negotiation domain, Search, Taverne

Citation

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 edn, Lecture Notes in Computer Science, vol. 13441 , Springer, Cham, pp. 67-83. https://doi.org/10.1007/978-3-031-20179-0_4