Bayesian Generalized Network Design

Authors Yuval Emek, Shay Kutten, Ron Lavi, Yangguang Shi

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Author Details

Yuval Emek
  • Faculty of Industrial Engineering and Management, Technion, Haifa, Israel
Shay Kutten
  • Faculty of Industrial Engineering and Management, Technion, Haifa, Israel
Ron Lavi
  • Faculty of Industrial Engineering and Management, Technion, Haifa, Israel
Yangguang Shi
  • Faculty of Industrial Engineering and Management, Technion, Haifa, Israel

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Yuval Emek, Shay Kutten, Ron Lavi, and Yangguang Shi. Bayesian Generalized Network Design. In 27th Annual European Symposium on Algorithms (ESA 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 144, pp. 45:1-45:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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.

Subject Classification

ACM Subject Classification
  • Theory of computation → Approximation algorithms analysis
  • Theory of computation → Mathematical optimization
  • Theory of computation → Algorithm design techniques
  • approximation algorithms
  • Bayesian competitive ratio
  • Bayesian ignorance
  • generalized network design
  • diseconomies of scale
  • energy consumption
  • smoothness
  • best response dynamics


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