Budget-Feasible Mechanisms for Submodular Welfare Maximization in Procurement Auctions
Shuang Cui, He Huang, Yu-e Sun, and Chen Xue

TL;DR
This paper introduces BFM-SWM, a novel budget-feasible mechanism for submodular welfare maximization in procurement auctions, with provable guarantees and improved efficiency over prior methods.
Contribution
It presents the first budget-feasible, truthful mechanism with approximation guarantees for submodular welfare maximization, improving deterministic ratios and computational efficiency.
Findings
BFM-SWM satisfies truthfulness, individual rationality, and non-negative surplus.
Achieves a deterministic approximation ratio of 1/(12+4√3) for submodular functions.
Reduces running time from O(n^2 log n) to O(n log n).
Abstract
Budget-feasible procurement auctions play a pivotal role in various AI-driven marketplaces, such as data acquisition and crowdsourcing, where a buyer with a limited budget seeks to procure services from strategic sellers with private costs. While numerous budget-feasible mechanisms have been proposed for the classic objective of maximizing the buyer's valuation, the more challenging and economically significant objective of social welfare maximization has only recently been studied, and existing approaches still sacrifice budget feasibility, thereby limiting their practical applicability. In this paper, we bridge this gap by proposing BFM-SWM, the first budget-feasible mechanism with provable approximation guarantees for submodular welfare maximization in procurement auctions. Our mechanism satisfies standard economic properties, including truthfulness, individual rationality, and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
