Multi-Attribute Proportional Representation
Lang, Jérôme; Skowron, Piotr (2016), Multi-Attribute Proportional Representation, in Schuurmans, Dale; Wellman, Michael, Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016), AAAI Press : Palo Alto (USA), p. 530-536
TypeCommunication / Conférence
Conference title30th AAAI Conference on Artificial Intelligence (AAAI 2016)
Conference cityPhoenix, Arizona
Conference countryUnited States
Book titleProceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016)
Book authorSchuurmans, Dale; Wellman, Michael
Number of pages4406
MetadataShow full item record
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
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.
Subjects / Keywordssocial choice; proportional representation; apportionment; approximation
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