Online random sampling for budgeted settings

Alon Eden*, Michal Feldman, Adi Vardi

*Corresponding author for this work

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

2 Scopus citations

Abstract

We study online multi-unit auctions in which each agent’s private type consists of the agent’s arrival and departure times, valuation function and budget. Similarly to secretary settings, the different attributes of the agents’ types are determined by an adversary, but the arrival process is random. We establish a general framework for devising truthful random sampling mechanisms for online multi-unit settings with budgeted agents. We demonstrate the applicability of our framework by applying it to different objective functions (revenue and liquid welfare), and a range of assumptions about the agents’ valuations (additive or general) and the items’ nature (divisible or indivisible). Our main result is the design of mechanisms for additive bidders with budget constraints that extract a constant fraction of the optimal revenue, for divisible and indivisible items (under a standard large market assumption). We also show a mechanism that extracts a constant fraction of the optimal liquid welfare for general valuations over divisible items.

Original languageEnglish
Title of host publicationAlgorithmic Game Theory - 10th International Symposium, SAGT 2017, Proceedings
EditorsVittorio Bilo, Michele Flammini
PublisherSpringer Verlag
Pages29-40
Number of pages12
ISBN (Print)9783319666990
DOIs
StatePublished - 2017
Event10th International Symposium on Algorithmic Game Theory, SAGT 2017 - L’Aquila, Italy
Duration: 12 Sep 201714 Sep 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10504 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Symposium on Algorithmic Game Theory, SAGT 2017
Country/TerritoryItaly
CityL’Aquila
Period12/09/1714/09/17

Funding

FundersFunder number
FP7/2007
Seventh Framework Programme337122
European Research Council
Seventh Framework Programme

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