Bayesian generalized network design

Yuval Emek; Shay Kutten; Ron Lavi; Yangguang Shi

doi:10.4230/LIPIcs.ESA.2019.45

Bayesian generalized network design

Yuval Emek, Shay Kutten, Ron Lavi, Yangguang Shi

Data and Decision Sciences

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

Abstract

We study network coordination problems, as captured by the setting of generalized network design (Emek et al., STOC 2018), in the face of uncertainty resulting from partial information that the network users hold regarding the actions of their peers. This uncertainty is formalized using Alon et al.’s Bayesian ignorance framework (TCS 2012). While the approach of Alon et al. is purely combinatorial, the current paper takes into account computational considerations: Our main technical contribution is the development of (strongly) polynomial time algorithms for local decision making in the face of Bayesian uncertainty.

Original language	English
Title of host publication	27th Annual European Symposium on Algorithms, ESA 2019
Editors	Michael A. Bender, Ola Svensson, Grzegorz Herman
ISBN (Electronic)	9783959771245
DOIs	https://doi.org/10.4230/LIPIcs.ESA.2019.45
State	Published - Sep 2019
Event	27th Annual European Symposium on Algorithms, ESA 2019 - Munich/Garching, Germany Duration: 9 Sep 2019 → 11 Sep 2019

Publication series

Name	Leibniz International Proceedings in Informatics, LIPIcs
Volume	144
ISSN (Print)	1868-8969

Conference

Conference	27th Annual European Symposium on Algorithms, ESA 2019
Country/Territory	Germany
City	Munich/Garching
Period	9/09/19 → 11/09/19

Keywords

Approximation algorithms
Bayesian competitive ratio
Bayesian ignorance
Best response dynamics
Diseconomies of scale
Energy consumption
Generalized network design
Smoothness

ASJC Scopus subject areas

Software

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10.4230/LIPIcs.ESA.2019.45

Cite this

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title = "Bayesian generalized network design",

abstract = "We study network coordination problems, as captured by the setting of generalized network design (Emek et al., STOC 2018), in the face of uncertainty resulting from partial information that the network users hold regarding the actions of their peers. This uncertainty is formalized using Alon et al.{\textquoteright}s Bayesian ignorance framework (TCS 2012). While the approach of Alon et al. is purely combinatorial, the current paper takes into account computational considerations: Our main technical contribution is the development of (strongly) polynomial time algorithms for local decision making in the face of Bayesian uncertainty.",

keywords = "Approximation algorithms, Bayesian competitive ratio, Bayesian ignorance, Best response dynamics, Diseconomies of scale, Energy consumption, Generalized network design, Smoothness",

author = "Yuval Emek and Shay Kutten and Ron Lavi and Yangguang Shi",

note = "Publisher Copyright: {\textcopyright} Yuval Emek, Shay Kutten, Ron Lavi, and Yangguang Shi.; 27th Annual European Symposium on Algorithms, ESA 2019 ; Conference date: 09-09-2019 Through 11-09-2019",

year = "2019",

month = sep,

doi = "10.4230/LIPIcs.ESA.2019.45",

language = "אנגלית",

series = "Leibniz International Proceedings in Informatics, LIPIcs",

editor = "Bender, {Michael A.} and Ola Svensson and Grzegorz Herman",

booktitle = "27th Annual European Symposium on Algorithms, ESA 2019",

}

Emek, Y, Kutten, S, Lavi, R & Shi, Y 2019, Bayesian generalized network design. in MA Bender, O Svensson & G Herman (eds), 27th Annual European Symposium on Algorithms, ESA 2019., 45, Leibniz International Proceedings in Informatics, LIPIcs, vol. 144, 27th Annual European Symposium on Algorithms, ESA 2019, Munich/Garching, Germany, 9/09/19. https://doi.org/10.4230/LIPIcs.ESA.2019.45

Bayesian generalized network design. / Emek, Yuval; Kutten, Shay; Lavi, Ron et al.
27th Annual European Symposium on Algorithms, ESA 2019. ed. / Michael A. Bender; Ola Svensson; Grzegorz Herman. 2019. 45 (Leibniz International Proceedings in Informatics, LIPIcs; Vol. 144).

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

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AU - Emek, Yuval

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AU - Lavi, Ron

AU - Shi, Yangguang

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AB - We study network coordination problems, as captured by the setting of generalized network design (Emek et al., STOC 2018), in the face of uncertainty resulting from partial information that the network users hold regarding the actions of their peers. This uncertainty is formalized using Alon et al.’s Bayesian ignorance framework (TCS 2012). While the approach of Alon et al. is purely combinatorial, the current paper takes into account computational considerations: Our main technical contribution is the development of (strongly) polynomial time algorithms for local decision making in the face of Bayesian uncertainty.

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KW - Bayesian ignorance

KW - Best response dynamics

KW - Diseconomies of scale

KW - Energy consumption

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KW - Smoothness

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Bayesian generalized network design

Abstract

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Keywords

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