Non-Clairvoyant Dynamic Mechanism Design with Budget Constraints and Beyond

37 Pages Posted: 10 Jun 2019 Last revised: 1 Jun 2021

See all articles by Yuan Deng

Yuan Deng

Duke University

Vahab Mirrokni

Google Research

Song Zuo

Google Research

Date Written: May 6, 2019

Abstract

We provide a general design framework for dynamic mechanisms under complex environments, coined Lossless History Compression mechanisms. Lossless history compression mechanisms compress the history into a state carrying the least historical information without losing any generality in terms of either revenue or welfare. In particular, the characterization works for almost arbitrary constraints on the outcomes, and any objective function defined on the historical reports, allocations, and the cumulative payments. We then apply our framework to design a non-clairvoyant dynamic mechanism under budget and ex-post individual rationality constraints that is dynamic incentive-compatible and achieves non-trivial revenue performance, even without any knowledge about the future. In particular, our dynamic mechanism obtains a constant approximation to the optimal dynamic mechanism having access to all information in advance. To the best of our knowledge, this is the first dynamic mechanism that achieves a constant approximation and strictly respects dynamic incentive-compatibility and budget constraints without relying on any forecasts of the future.

Keywords: dynamic mechanism design, general constraints, public correlation, repeated auctions, budget, non-clairvoyance, bank account mechanisms

JEL Classification: D44, C73, D82

Suggested Citation

Deng, Yuan and Mirrokni, Vahab and Zuo, Song, Non-Clairvoyant Dynamic Mechanism Design with Budget Constraints and Beyond (May 6, 2019). Available at SSRN: https://ssrn.com/abstract=3383231 or http://dx.doi.org/10.2139/ssrn.3383231

Yuan Deng

Duke University ( email )

100 Fuqua Drive
Durham, NC 27708-0204
United States

Vahab Mirrokni

Google Research ( email )

Song Zuo (Contact Author)

Google Research ( email )

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