Approval-Based Committee Voting under Incomplete Information

Aviram Imber, Jonas Israel, Markus Brill, Benny Kimelfeld

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

Abstract

We investigate approval-based committee voting with incomplete information about the approval preferences of voters. We consider several models of incompleteness where each voter partitions the set of candidates into approved, disapproved, and unknown candidates, possibly with ordinal preference constraints among candidates in the latter category. This captures scenarios where voters have not evaluated all candidates and/or it is unknown where voters draw the threshold between approved and disapproved candidates. We study the complexity of some fundamental computational problems for a number of classic approval-based committee voting rules including Proportional Approval Voting and Chamberlin-Courant. These problems include that of determining whether a given set of candidates is a possible or necessary winning committee and whether it forms a committee that possibly or necessarily satisfies representation axioms. We also consider the problem whether a given candidate is possibly or necessarily a member of the winning committee.

Original languageEnglish
Title of host publicationAAAI-22 Technical Tracks 5
Pages5076-5083
Number of pages8
ISBN (Electronic)1577358767, 9781577358763
DOIs
StatePublished - 30 Jun 2022
Event36th AAAI Conference on Artificial Intelligence, AAAI 2022 - Virtual, Online
Duration: 22 Feb 20221 Mar 2022

Publication series

NameProceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022
Volume36

Conference

Conference36th AAAI Conference on Artificial Intelligence, AAAI 2022
CityVirtual, Online
Period22/02/221/03/22

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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