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arXiv · 1207.1360

Models for Truthful Online Double Auctions

Jonathan Bredin·David C. Parkes
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Abstract

Online double auctions (DAs) model a dynamic two-sided matching problem with private information and self-interest, and are relevant for dynamic resource and task allocation problems. We present a general method to design truthful DAs, such that no agent can benefit from misreporting its arrival time, duration, or value. The family of DAs is parameterized by a pricing rule, and includes a generalization of McAfee's truthful DA to this dynamic setting. We present an empirical study, in which we study the allocative-surplus and agent surplus for a number of different DAs. Our results illustrate that dynamic pricing rules are important to provide good market efficiency for markets with high volatility or low volume.

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Jonathan Bredin, David C. Parkes. 2012-07-04. Models for Truthful Online Double Auctions. https://arxiv.org/abs/1207.1360

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