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Budget Feasible Mechanisms: A Survey

  • Xiang Liu
  • , Hau Chan
  • , Minming Li
  • , Weiwei Wu*
  • *Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

In recent decades, the design of budget feasible mechanisms for a wide range of procurement auction settings has received significant attention in the Artificial Intelligence (AI) community. These procurement auction settings have practical applications in various domains such as federated learning, crowdsensing, edge computing, and resource allocation. In a basic procurement auction setting of these domains, a buyer with a limited budget is tasked with procuring items (e.g., goods or services) from strategic sellers, who have private information on the true costs of their items and incentives to misrepresent their items' true costs. The primary goal of budget feasible mechanisms is to elicit the true costs from sellers and determine items to procure from sellers to maximize the buyer valuation function for the items and ensure that the total payment to the sellers is no more than the budget. In this survey, we provide a comprehensive overview of key procurement auction settings and results of budget feasible mechanisms. We provide several promising future research directions. © 2024 International Joint Conferences on Artificial Intelligence. All rights reserved.
Original languageEnglish
Title of host publicationProceedings of the Thirty-Third International Joint Conference on Artificial Intelligence
EditorsKate Larson
PublisherInternational Joint Conferences on Artificial Intelligence
Pages8132-8141
ISBN (Electronic)9781956792041
DOIs
Publication statusPublished - Aug 2024
Event33rd International Joint Conference on Artificial Intelligence (IJCAI 2024) - International Convention Center Jeju, Jeju Island, Korea, Republic of
Duration: 3 Aug 2024 → 9 Aug 2024
https://ijcai24.org

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823

Conference

Conference33rd International Joint Conference on Artificial Intelligence (IJCAI 2024)
Abbreviated titleIJCAI-24
PlaceKorea, Republic of
CityJeju Island
Period3/08/24 → 9/08/24
Internet address

Bibliographical note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

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