审批制委员会投票中的多元代表

中文摘要 AI 辅助

审批制委员会（ABC）投票的研究迄今主要聚焦于比例代表制。基于Chamberlin--Courant分数的多元代表的经典概念，统计委员会中至少拥有一位代表的选民数量，使其成为一种个体主义的观念。我们发展了一个更为全面的理论，转而要求许多选民群体的代表，将其基于合理代表（JR）公理，并在两个方向上加强该公理。首先，我们研究了现有的强合理代表（SJR）和半强合理代表（SSJR）公理，它们考虑与JR相同的凝聚力群体，但要求更严格的代表。我们证明，在一般域上，这两者都无法高效优化（除非P=NP），但在候选区间域上两者均可优化。其次，为了捕捉群体独特且具有定义性的观点，我们引入了独特代表（DR）及其局部优化变体局部DR。我们解决了可满足性和计算时间问题，并表明（局部）DR与已知的比例性和多元性公理不同。在真实世界和合成数据上的实验表明，局部DR在多个经验多元性度量上表现良好。

英文摘要

The study of approval-based committee (ABC) voting has so far focused predominantly on proportional representation. The canonical notion of diverse representation, based on the Chamberlin--Courant score, counts the number of voters with at least one representative in the committee, making it an individualistic notion. We develop a more comprehensive theory that instead requires the representation of many groups of voters, grounding it in the justified representation (JR) axiom, which we strengthen in two directions. First, we study the existing axioms of Strong JR (SJR) and Semi-Strong JR (SSJR), which consider the same cohesive groups as JR but demand stricter representation. We show that neither can be optimized efficiently on general domains (unless P=NP), but both can be on the Candidate Interval domain. Second, to capture the unique and defining opinions of a group, we introduce Distinctive Representation (DR) and its local optimization variant, Local DR. We address satisfiability and computation time, and show (Local) DR to be distinct from known proportionality and diversity axioms. Experiments on real-world and synthetic data show Local DR performs well on multiple empirical measures of diversity.

发表机构

• Rijksuniversiteit Groningen（格罗宁根大学）
• WU Wien（维也纳经济大学）

机构由 AI 辅助整理，请以论文原文为准。