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Multi-Attribute Proportional Representation

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12002-55497-1-PB.pdf (683.5Kb)
Date
2016
Dewey
Recherche opérationnelle
Sujet
social choice; proportional representation; apportionment; approximation
Conference name
30th AAAI Conference on Artificial Intelligence (AAAI 2016)
Conference date
02-2016
Conference city
Phoenix, Arizona
Conference country
United States
Book title
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016)
Author
Schuurmans, Dale; Wellman, Michael
Publisher
AAAI Press
Publisher city
Palo Alto (USA)
Year
12-2016
Pages number
4406
ISBN
978-1-57735-760-5
URI
https://basepub.dauphine.fr/handle/123456789/16477
Collections
  • LAMSADE : Publications
Metadata
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Author
Lang, Jérôme
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Skowron, Piotr
98120 Oxford University
Type
Communication / Conférence
Item number of pages
530-536
Abstract (EN)
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 fit. 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 boils down to the apportionment problem for party-list proportional representation systems (in such case the value of the single attribute is the political affiliation of a candidate). We study some properties of the associated subset selection rules, and address their computation.

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