Enabling negotiating agents to explore very large outcome spaces
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.
|Lecture Notes in Artificial Intelligence|
|2022 International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2022|
|Organisation||Centrum Wiskunde & Informatica, Amsterdam (CWI), The Netherlands|
Koca, T, Jonker, C.M, & Baarslag, T. (2022). Enabling negotiating agents to explore very large outcome spaces. In Autonomous Agents and Multiagent Systems. Best and Visionary Papers. AAMAS 2022 (pp. 67–83). doi:10.1007/978-3-031-20179-0_4