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Multi-Winner Reconfiguration

  • Jiehua Chen
  • , Christian Hatschka
  • , Sofia Simola

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

We introduce a multi-winner reconfiguration model to examine how to transition between two subsets of alternatives (aka. committees) through a sequence of minor yet impactful modifications, called reconfiguration path. We analyze this model under four approval-based voting rules: Chamberlin-Courant (CC), Proportional Approval Voting (PAV), Approval Voting (AV), and Satisfaction Approval Voting (SAV). The problem exhibits computational intractability for CC and PAV, and polynomial solvability for AV and SAV. We provide a detailed multivariate complexity analysis for CC and PAV, demonstrating that although the problem remains challenging in many scenarios, there are specific cases that allow for efficient parameterized algorithms.

Original languageEnglish
JournalAdvances in Neural Information Processing Systems
Volume37
StatePublished - 1 Jan 2024
Externally publishedYes
Event38th Conference on Neural Information Processing Systems, NeurIPS 2024 - Vancouver, Canada
Duration: 9 Dec 202415 Dec 2024

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Computer Networks and Communications

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