Approximation algorithms for BalancedCC multiwinner rules

Markus Brill, Piotr Faliszewski, Frank Sommer, Nimrod Talmon

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

4 Scopus citations

Abstract

X-BalancedCC multiwinner voting rules constitute an attractive but computationally intractable compromise between the proportionality provided by the Monroe rule and the diversity provided by the Chamberlin-Courant rule. We show how to use the Greedy-Monroe algorithm to get improved approximation results for the X-BalancedCC rules and for the Chamberlin-Courant rule, by appropriately setting a "schedule" for the sizes of virtual districts. We describe a polynomial-time algorithm for computing a schedule that guarantees high approximation ratio, but show that finding the best possible schedule for a given election is NP-hard. We further evaluate our algorithms experimentally and show that they perform very well in practice.

Original languageEnglish
Title of host publication18th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2019
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages494-502
Number of pages9
ISBN (Electronic)9781510892002
StatePublished - 1 Jan 2019
Event18th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2019 - Montreal, Canada
Duration: 13 May 201917 May 2019

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume1
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

Conference18th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2019
Country/TerritoryCanada
CityMontreal
Period13/05/1917/05/19

Keywords

  • Approximation algorithms
  • Chamberlin-Courant rule
  • Greedy algorithms
  • Monroe rule
  • Multiwinner elections

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