Lune

SODA2022顶会

Approximate Core for Committee Selection via Multilinear Extension and Market Clearing

Kamesh Munagala, Yiheng Shen, Kangning Wang, Zhiyi Wang

2022年份
14被引次数
5顶会引用

摘要

Motivated by civic problems such as participatory budgeting and multiwinner elections, we consider the problem of public good allocation: Given a set of indivisible projects (or candidates) of different sizes, and voters with different monotone utility functions over subsets of these candidates, the goal is to choose a budget-constrained subset of these candidates (or a committee) that provides fair utility to the voters. The notion of fairness we adopt is that of core stability from cooperative game theory: No subset of voters should be able to choose another blocking committee of proportionally smaller size that provides strictly larger utility to all voters that deviate. The core provides a strong notion of fairness, subsuming other notions that have been widely studied in computational social choice.

It is well-known that an exact core need not exist even when utility functions of the voters are additive across candidates. We therefore relax the problem to allow approximation: Voters can only deviate to the blocking committee if after they choose any extra candidate (called an additament ), their utility still increases by an α factor. If no blocking committee exists under this definition, we call this an α-core.

Our main result is that an α-core, for α < 67.37, always exists when utilities of the voters are arbitrary monotone submodular functions, and this can be computed in polynomial time. This result improves to α < 9.27 for additive utilities, albeit without the polynomial time guarantee. Our results are a significant improvement over prior work that only shows logarithmic approximations for the case of additive utilities. We complement our results with a lower bound of α > 1.015 for submodular utilities, and a lower bound of any function in the number of voters and candidates for general monotone utilities.

问问这篇 Paper

智能体会读完全文。

Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。

可以从这些问题问起

智能体调用

Luneget_paper_fulltext

在 Lune 里问

免费开始,无需绑卡

引用它的顶会 Paper5

问问它们各自怎么用它

它引用的顶会 Paper2

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖