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.

Gradient-based local formulations of the Vickrey–Clarke–Groves mechanism for truthful minimization of social convex objectives / Angeli David; Manfredi Sabato. - In: AUTOMATICA. - ISSN 0005-1098. - ELETTRONICO. - 150:(2023), pp. 0-0. [10.1016/j.automatica.2023.110870]

Gradient-based local formulations of the Vickrey–Clarke–Groves mechanism for truthful minimization of social convex objectives

Angeli David;
2023

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.
2023
150
0
0
Angeli David; Manfredi Sabato
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1301539
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