Bicriteria Multidimensional Mechanism Design with Side Information
We develop a versatile methodology for multidimensional mechanism design that incorporates side information about agents to generate high welfare and high revenue simultaneously. Side information sources include advice from domain experts, predictions from machine learning models, and even the mecha...
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Main Authors | , , |
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Format | Journal Article |
Language | English |
Published |
27.02.2023
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Subjects | |
Online Access | Get full text |
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Summary: | We develop a versatile methodology for multidimensional mechanism design that
incorporates side information about agents to generate high welfare and high
revenue simultaneously. Side information sources include advice from domain
experts, predictions from machine learning models, and even the mechanism
designer's gut instinct. We design a tunable mechanism that integrates side
information with an improved VCG-like mechanism based on weakest types, which
are agent types that generate the least welfare. We show that our mechanism,
when carefully tuned, generates welfare and revenue competitive with the
prior-free total social surplus, and its performance decays gracefully as the
side information quality decreases. We consider a number of side information
formats including distribution-free predictions, predictions that express
uncertainty, agent types constrained to low-dimensional subspaces of the
ambient type space, and the traditional setting with known priors over agent
types. In each setting we design mechanisms based on weakest types and prove
performance guarantees. |
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DOI: | 10.48550/arxiv.2302.14234 |