Near-Tight Algorithms for the Chamberlin-Courant and Thiele Voting Rules

Krzysztof Sornat, Virginia Vassilevska Williams, Yinzhan Xu

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

2 Scopus citations

Abstract

We present an almost optimal algorithm for the classic Chamberlin-Courant multiwinner voting rule (CC) on single-peaked preference profiles. Given n voters and m candidates, it runs in almost linear time in the input size improving the previous best O(nm2) time algorithm. We also study multiwinner voting rules on nearly single-peaked preference profiles in terms of the candidate-deletion operation. We show a polynomial-time algorithm for CC where a given candidate-deletion set D has logarithmic size. Actually, our algorithm runs in 2|D|· poly(n, m) time and the base of the power cannot be improved under the Strong Exponential Time Hypothesis. We also adapt these results to all non-constant Thiele rules which generalize CC with approval ballots.

Original languageEnglish
Title of host publicationProceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022
EditorsLuc De Raedt, Luc De Raedt
PublisherInternational Joint Conferences on Artificial Intelligence
Pages482-488
Number of pages7
ISBN (Electronic)9781956792003
StatePublished - 1 Jan 2022
Externally publishedYes
Event31st International Joint Conference on Artificial Intelligence, IJCAI 2022 - Vienna, Austria
Duration: 23 Jul 202229 Jul 2022

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823

Conference

Conference31st International Joint Conference on Artificial Intelligence, IJCAI 2022
Country/TerritoryAustria
CityVienna
Period23/07/2229/07/22

ASJC Scopus subject areas

  • Artificial Intelligence

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