@inproceedings{9fd1cda71d2c444ca818a4be6f4071ca,
title = "Auctions between Regret-Minimizing Agents",
abstract = "We analyze a scenario in which software agents implemented as regret-minimizing algorithms engage in a repeated auction on behalf of their users. We study first-price and second-price auctions, as well as their generalized versions (e.g., as those used for ad auctions). Using both theoretical analysis and simulations, we show that, surprisingly, in second-price auctions the players have incentives to misreport their true valuations to their own learning agents, while in first-price auctions it is a dominant strategy for all players to truthfully report their valuations to their agents.",
keywords = "Auctions, Regret Minimization, Repeated Games",
author = "Yoav Kolumbus and Noam Nisan",
note = "Publisher Copyright: {\textcopyright} 2022 ACM.; 31st ACM World Wide Web Conference, WWW 2022 ; Conference date: 25-04-2022 Through 29-04-2022",
year = "2022",
month = apr,
day = "25",
doi = "10.1145/3485447.3512055",
language = "الإنجليزيّة",
series = "WWW 2022 - Proceedings of the ACM Web Conference 2022",
pages = "100--111",
booktitle = "WWW '22",
}