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On the Complexity of Finding a Diverse and Representative Committee using a Monotone, Separable Positional Multiwinner Voting Rule

arXiv 2211.13217 ↗First posted 23 Nov 2022cs.GT cs.AI cs.CCcited by 0

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Abstract (arXiv)

Fairness in multiwinner elections, a growing line of research in computational social choice, primarily concerns the use of constraints to ensure fairness. Recent work proposed a model to find a diverse and representative committee and studied the model's computational aspects. However, the work gave complexity results under major assumptions on how the candidates and the voters are grouped. Here, we close this gap and classify the complexity of finding a diverse and representative committee using a monotone, separable positional multiwinner voting rule, conditioned only on the assumption that P neq NP.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 20 references that are in the map. First posted on arXiv 23 Nov 2022.

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6 of 20 references.

References · 6

  1. 2017Multiwinner Elections with Diversity Constraintscited by 10
  2. 2019Group Fairness in Committee Selectioncited by 10
  3. 2021District-Fair Participatory Budgetingcited by 4
  4. 2014Determining Possible and Necessary Winners Given Partial Orderscited by 3
  5. 2021DiRe Committee : Diversity and Representation Constraints in Multiwinner Electionscited by 3
  6. 2018The Complexity of the Possible Winner Problem over Partitioned Preferencescited by 1

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