Gradient-based local formulations of the Vickrey-Clarke-Groves mechanism for truthful minimization of social convex objectives
File(s)Social_Optimisation (9).pdf (449.25 KB)
Accepted version
Author(s)
Angeli, David
Manfredi, Sabato
Type
Journal Article
Abstract
We propose a gradient-based iterative method yielding a truthfulness preserving implementation of the Vickrey–Clarke–Groves mechanism for minimization of social convex objectives. The approach is guaranteed to return, in the limit, the same efficient outcomes of the VCG method, while improving its privacy limitations and reducing its communication requirements. Its performance is investigated through an illustrative example of vehicles coordination.
Date Issued
2023-02-02
Date Acceptance
2022-12-16
Citation
Automatica, 2023, 150, pp.1-9
ISSN
0005-1098
Publisher
Elsevier
Start Page
1
End Page
9
Journal / Book Title
Automatica
Volume
150
Copyright Statement
Copyright © Elsevier Ltd. All rights reserved. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
Identifier
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000930837800001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
ALGORITHM
Automation & Control Systems
DISTRIBUTED OPTIMIZATION
EFFICIENCY
Engineering
Engineering, Electrical & Electronic
Science & Technology
Technology
Publication Status
Published
Article Number
ARTN 110870
Date Publish Online
2023-02-02