On the Complexity of Winner Verification and Candidate Winner for Multiwinner Voting Rules

On the Complexity of Winner Verification and Candidate Winner for Multiwinner Voting Rules

Chinmay Sonar, Palash Dey, Neeldhara Misra

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence

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) dissatisfaction 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 Theta_2^P. Our contribution fills an essential gap in the literature for these important multi-winner rules.
Keywords:
Agent-based and Multi-agent Systems: Computational Social Choice
Agent-based and Multi-agent Systems: Voting