Farhadi, Farzaneh, Chli, Maria and Jennings, Nicholas R. (2023). Optimal and Efficient Auctions for the Gradual Procurement of Strategic Service Provider Agents. Journal of Artificial Intelligence Research, 76 , pp. 959-1018.
Abstract
We consider an outsourcing problem where a software agent procures multiple services from providers with uncertain reliabilities to complete a computational task before a strict deadline. The service consumer’s goal is to design an outsourcing strategy (defining which services to procure and when) so as to maximize a specific objective function. This objective function can be different based on the consumer’s nature; a socially-focused consumer often aims to maximize social welfare, while a self-interested consumer often aims to maximize its own utility. However, in both cases, the objective function depends on the providers’ execution costs, which are privately held by the self-interested providers and hence may be misreported to influence the consumer’s decisions. For such settings, we develop a unified approach to design truthful procurement auctions that can be used by both socially-focused and, separately, self-interested consumers. This approach benefits from our proposed weighted threshold payment scheme which pays the provably minimum amount to make an auction with a monotone outsourcing strategy incentive compatible. This payment scheme can handle contingent outsourcing plans, where additional procurement happens gradually over time and only if the success probability of the already hired providers drops below a time-dependent threshold. Using a weighted threshold payment scheme, we design two procurement auctions that maximize, as well as two low-complexity heuristic-based auctions that approximately maximize, the consumer’s expected utility and expected social welfare, respectively. We demonstrate the effectiveness and strength of our proposed auctions through both game-theoretical and empirical analysis.
Publication DOI: | https://doi.org/10.1613/jair.1.14126 |
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Divisions: | College of Engineering & Physical Sciences College of Engineering & Physical Sciences > Systems analytics research institute (SARI) ?? 50811700Jl ?? College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies > Applied AI & Robotics College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies College of Engineering & Physical Sciences > Aston Centre for Artifical Intelligence Research and Application |
Additional Information: | Copyright © 2023, AI Access Foundation. This article is the published version of the article, "Farhadi, Farzaneh, Chli, Maria and Jennings, Nicholas R. (2023). Optimal and Efficient Auctions for the Gradual Procurement of Strategic Service Provider Agents. Journal of Artificial Intelligence Research, 76 , pp. 959-1018, made available in accordance with the JAIR License 1.0 [https://www.jair.org/index.php/jair/oldlicense]. |
Uncontrolled Keywords: | game theory, multiagent systems,Artificial Intelligence |
Publication ISSN: | 1076-9757 |
Last Modified: | 07 Oct 2024 07:47 |
Date Deposited: | 16 Jun 2023 09:48 |
Full Text Link: | |
Related URLs: |
https://www.jai ... icle/view/14126
(Publisher URL) http://www.scop ... tnerID=8YFLogxK (Scopus URL) |
PURE Output Type: | Article |
Published Date: | 2023-04-14 |
Accepted Date: | 2023-04-01 |
Submitted Date: | 2022-08 |
Authors: |
Farhadi, Farzaneh
(
0000-0002-1201-3074)
Chli, Maria ( 0000-0002-2840-4475) Jennings, Nicholas R. |