Pricing online decisions: Beyond auctions

Ilan Reuven Cohen, Alon Eden, Amos Fiat, Łukasz Jez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Scopus citations


We consider dynamic pricing schemes in online settings where selfish agents generate online events. Previous work on online mechanisms has dealt almost entirely with the goal of maximizing social welfare or revenue in an auction settings. This paper deals with quite general settings and minimizing social costs. We show that appropriately computed posted prices allow one to achieve essentially the same performance as the best online algorithm. This holds in a wide variety of settings. Unlike online algorithms that learn about the event, and then make en-forcable decisions, prices are posted without knowing the future events or even the current event, and are thus inherently dominant strategy incentive compatible. In particular we show that one can give efficient posted price mechanisms for metrical task systems, some instances of the κ-server problem, and metrical matching problems. We give both deterministic and randomized algorithms. Such posted price mechanisms decrease the social cost dramatically over selfish behavior where no decision incurs a charge. One alluring application of this is reducing the social cost of free parking exponentially.

Original languageAmerican English
Title of host publicationProceedings of the 26th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2015
PublisherAssociation for Computing Machinery
Number of pages19
ISBN (Electronic)9781611973747
StatePublished - 2015
Externally publishedYes
Event26th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2015 - San Diego, United States
Duration: 4 Jan 20156 Jan 2015

Publication series

NameProceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms


Conference26th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2015
Country/TerritoryUnited States
CitySan Diego

Bibliographical note

Publisher Copyright:
Copyright © 2015 by the Society for Industrial and Applied Mathmatics.


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