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The Price of Justified Representation

Ayumi Igarashi
Edith Elkind
Piotr Faliszewski
Ulrike Schmidt-Kraepelin
Warut Suksompong
AAAI 2022
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In multiwinner approval voting, the goal is to select k-member committees based on voters' approval ballots. A well-studied concept of proportionality in this context is the justified representation (JR) axiom, which demands that no large cohesive group of voters remains unrepresented. However, the JR axiom may conflict with other desiderata, such as coverage (maximizing the number of voters who approve at least one committee member) or social welfare (maximizing the number of approvals obtained by committee members). In this work, we investigate the impact of the JR axiom (as well as the more demanding EJR axiom) on social welfare and coverage. Our approach is threefold: we derive worst-case bounds on the loss of welfare/coverage that is caused by imposing JR, study the algorithmic complexity of finding 'good' committees that provide JR (obtaining a hardness result, an approximation algorithm, and a positive result for the one-dimensional setting), and study this problem empirically on several synthetic datasets.