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Strategyproofness and Proportionality in Party-Approval Multiwinner Elections

  • Theo Delemazure*
  • , Tom Demeulemeester
  • , Manuel Eberl
  • , Jonas Israel
  • , Patrick Lederer
  • *Corresponding author for this work

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

Abstract

In party-approval multiwinner elections the goal is to allocate the seats of a fixed-size committee to parties based on the approval ballots of the voters over the parties. In particular, each voter can approve multiple parties and each party can be assigned multiple seats. Two central requirements in this setting are proportional representation and strategyproofness. Intuitively, proportional representation requires that every sufficiently large group of voters with similar preferences is represented in the committee. Strategyproofness demands that no voter can benefit by misreporting her true preferences. We show that these two axioms are incompatible for anonymous party-approval multiwinner voting rules, thus proving a far-reaching impossibility theorem. The proof of this result is obtained by formulating the problem in propositional logic and then letting a SAT solver show that the formula is unsatisfiable. Additionally, we demonstrate how to circumvent this impossibility by considering a weakening of strategyproofness which requires that only voters who do not approve any elected party cannot manipulate. While most common voting rules fail even this weak notion of strategyproofness, we characterize Chamberlin-Courant approval voting within the class of Thiele rules based on this strategyproofness notion.
Original languageEnglish
Title of host publicationProceedings of the 37th AAAI conference on artificial intelligence
EditorsBrian Williams, Yiling Chen, Jennifer Neville
Pages5591-5599
Number of pages9
Volume37
ISBN (Electronic)9781577358800
DOIs
Publication statusPublished - 27 Jun 2023
Externally publishedYes
Event37th AAAI Conference on Artificial Intelligence (AAAI) / 35th Conference on Innovative Applications of Artificial Intelligence / 13th Symposium on Educational Advances in Artificial Intelligence - Washington, DC, United States
Duration: 7 Feb 202314 Feb 2023
https://aaai.org/the-37th-aaai-conference-on-artificial-intelligence-aims-to-build-bridges/

Publication series

SeriesProceedings of the AAAI Conference on Artificial Intelligence
Number5
Volume37
ISSN2159-5399

Conference

Conference37th AAAI Conference on Artificial Intelligence (AAAI) / 35th Conference on Innovative Applications of Artificial Intelligence / 13th Symposium on Educational Advances in Artificial Intelligence
Abbreviated titleAAAI 2023
Country/TerritoryUnited States
CityWashington, DC
Period7/02/2314/02/23
Internet address

Keywords

  • GTEP
  • SOCIAL CHOICE
  • voting

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