Online random sampling for budgeted settings

Alon Eden; Michal Feldman; Adi Vardi

doi:10.1007/978-3-319-66700-3_3

Online random sampling for budgeted settings

Alon Eden^*, Michal Feldman, Adi Vardi

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	Algorithmic Game Theory - 10th International Symposium, SAGT 2017, Proceedings
Editors	Vittorio Bilo, Michele Flammini
Publisher	Springer Verlag
Pages	29-40
Number of pages	12
ISBN (Print)	9783319666990
DOIs	https://doi.org/10.1007/978-3-319-66700-3_3
State	Published - 2017
Externally published	Yes
Event	10th International Symposium on Algorithmic Game Theory, SAGT 2017 - L’Aquila, Italy Duration: 12 Sep 2017 → 14 Sep 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10504 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th International Symposium on Algorithmic Game Theory, SAGT 2017
Country/Territory	Italy
City	L’Aquila
Period	12/09/17 → 14/09/17

Bibliographical note

Publisher Copyright:
© Springer International Publishing AG 2017.

Access to Document

10.1007/978-3-319-66700-3_3

Cite this

Eden, A., Feldman, M., & Vardi, A. (2017). Online random sampling for budgeted settings. In V. Bilo, & M. Flammini (Eds.), Algorithmic Game Theory - 10th International Symposium, SAGT 2017, Proceedings (pp. 29-40). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10504 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-66700-3_3

Eden, Alon ; Feldman, Michal ; Vardi, Adi. / Online random sampling for budgeted settings. Algorithmic Game Theory - 10th International Symposium, SAGT 2017, Proceedings. editor / Vittorio Bilo ; Michele Flammini. Springer Verlag, 2017. pp. 29-40 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "We study online multi-unit auctions in which each agent{\textquoteright}s private type consists of the agent{\textquoteright}s arrival and departure times, valuation function and budget. Similarly to secretary settings, the different attributes of the agents{\textquoteright} 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{\textquoteright} valuations (additive or general) and the items{\textquoteright} 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.",

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Eden, A, Feldman, M & Vardi, A 2017, Online random sampling for budgeted settings. in V Bilo & M Flammini (eds), Algorithmic Game Theory - 10th International Symposium, SAGT 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10504 LNCS, Springer Verlag, pp. 29-40, 10th International Symposium on Algorithmic Game Theory, SAGT 2017, L’Aquila, Italy, 12/09/17. https://doi.org/10.1007/978-3-319-66700-3_3

Online random sampling for budgeted settings. / Eden, Alon; Feldman, Michal; Vardi, Adi.
Algorithmic Game Theory - 10th International Symposium, SAGT 2017, Proceedings. ed. / Vittorio Bilo; Michele Flammini. Springer Verlag, 2017. p. 29-40 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10504 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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Eden A, Feldman M, Vardi A. Online random sampling for budgeted settings. In Bilo V, Flammini M, editors, Algorithmic Game Theory - 10th International Symposium, SAGT 2017, Proceedings. Springer Verlag. 2017. p. 29-40. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-66700-3_3

Online random sampling for budgeted settings

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