English

Multi-Attribute Proportional Representation

Artificial Intelligence 2021-03-29 v2 Data Structures and Algorithms Computer Science and Game Theory

Abstract

We consider the following problem in which a given number of items has to be chosen from a predefined set. Each item is described by a vector of attributes and for each attribute there is a desired distribution that the selected set should have. We look for a set that fits as much as possible the desired distributions on all attributes. Examples of applications include choosing members of a representative committee, where candidates are described by attributes such as sex, age and profession, and where we look for a committee that for each attribute offers a certain representation, i.e., a single committee that contains a certain number of young and old people, certain number of men and women, certain number of people with different professions, etc. With a single attribute the problem collapses to the apportionment problem for party-list proportional representation systems (in such case the value of the single attribute would be a political affiliation of a candidate). We study the properties of the associated subset selection rules, as well as their computation complexity.

Keywords

Cite

@article{arxiv.1509.03389,
  title  = {Multi-Attribute Proportional Representation},
  author = {Jerome Lang and Piotr Skowron},
  journal= {arXiv preprint arXiv:1509.03389},
  year   = {2021}
}
R2 v1 2026-06-22T10:54:18.181Z