On the complexity of Winner Verification and Candidate Winner for Multiwinner Voting Rules
April 29, 2020 Β· Declared Dead Β· π International Joint Conference on Artificial Intelligence
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Authors
Chinmay Sonar, Palash Dey, Neeldhara Misra
arXiv ID
2004.13933
Category
cs.DS: Data Structures & Algorithms
Cross-listed
cs.GT
Citations
5
Venue
International Joint Conference on Artificial Intelligence
Last Checked
3 months ago
Abstract
The Chamberlin-Courant and Monroe rules are fundamental and well-studied rules in the literature of multi-winner elections. The problem of determining if there exists a committee of size k that has a Chamberlin-Courant (respectively, Monroe) score of at most r is known to be NP-complete. We consider the following natural problems in this setting: a) given a committee S of size k as input, is it an optimal k-sized committee, and b) given a candidate c and a committee size k, does there exist an optimal k-sized committee that contains c? In this work, we resolve the complexity of both problems for the Chamberlin-Courant and Monroe voting rules in the settings of rankings as well as approval ballots. We show that verifying if a given committee is optimal is coNP-complete whilst the latter problem is complete for $Ξ_{2}^{P}$. We also demonstrate efficient algorithms for the second problem when the input consists of single-peaked rankings. Our contribution fills an essential gap in the literature for these important multi-winner rules.
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