@inproceedings{13213c3e817f4b1086afe3fc050e09b7,
title = "Enabling Negotiating Agents to Explore Very Large Outcome Spaces",
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\textasciicircum{}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.",
author = "Thimjo Ko{\c c}a and Jonker, \{Catholijn M.\} and Tim Baarslag",
year = "2022",
month = nov,
day = "6",
doi = "10.1007/978-3-031-20179-0\_4",
language = "English",
isbn = "978-3-031-20178-3",
series = "Lecture Notes in Computer Science (LNCS)",
publisher = "Springer",
pages = "67--83",
editor = "Melo, \{Francisco S.\} and Fei Fang",
booktitle = "Autonomous Agents and Multiagent Systems. Best and Visionary Papers",
address = "Germany",
note = "Workshops on OptLearn-MAS, MABS, ABMUS, EMAS, and RAD-AI, held at the 21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022 ; Conference date: 09-05-2022 Through 13-05-2022",
}