Enabling Negotiating Agents to Explore Very Large Outcome Spaces

Conference paper (2022)

Authors

Thimjo Koca Universiteit van Amsterdam
Tim Baarslag Centrum Wiskunde & Informatica (CWI), Universiteit Utrecht
Catholijn M. Jonker Universiteit Leiden, Interactive Intelligence - EEMCS
Research Group
Interactive Intelligence (EEMCS) (TU Delft)
Copyright: © 2022 Thimjo Koca, Tim Baarslag, C.M. Jonker
DOI: https://doi.org/0.1007/978-3-031-20179-0_4
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Published Date

2022

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Interactive Intelligence

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
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- Embargo expired in 10-04-2023
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