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Combinatorial cost sharing

Shahar Dobzinski, Shahar Ovadia

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

Abstract

We introduce a combinatorial variant of the cost sharing problem: several services can be provided to each player and each player values every combination of services differently. A publicly known cost function specifies the cost of providing every possible combination of services. A combinatorial cost sharing mechanism is a protocol that decides which services each player gets and at what price. We look for dominant strategy mechanisms that are (economically) efficient and cover the cost, ideally without overcharging (i.e., budget balanced). Note that unlike the standard cost sharing se.ing, combinatorial cost sharing is a multi-parameter domain. .is makes designing dominant strategy mechanisms with good guarantees a challenging task. We present the Potential Mechanism -A combination of the VCG mechanism and a well-known tool from the theory of cooperative games: Hart and Mas-Colell's potential function. .e potential mechanism is a dominant strategy mechanism that always covers the incurred cost. When the cost function is subadditive the same mechanism is also approximately efficient. Our main technical contribution shows that when the cost function is submodular the potential mechanism is approximately budget balanced in three settings: supermodular valuations, symmetric cost function and general symmetric valuations, and two players with general valuations.

Original languageEnglish
Title of host publicationEC 2017 - Proceedings of the 2017 ACM Conference on Economics and Computation
Pages387-404
Number of pages18
ISBN (Electronic)9781450345279
DOIs
StatePublished - 20 Jun 2017
Event18th ACM Conference on Economics and Computation, EC 2017 - Cambridge, United States
Duration: 26 Jun 201730 Jun 2017

Publication series

NameEC 2017 - Proceedings of the 2017 ACM Conference on Economics and Computation

Conference

Conference18th ACM Conference on Economics and Computation, EC 2017
Country/TerritoryUnited States
CityCambridge
Period26/06/1730/06/17

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Statistics and Probability
  • Computational Mathematics
  • Economics and Econometrics

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