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Voting with Rank Dependent Scoring Rules

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Date
2014
Link to item file
http://www.aaai.org/ocs/index.php/AAAI/AAAI14/paper/view/8549
Dewey
Recherche opérationnelle
Sujet
social choice; voting
Conference name
28th AAAI Conference on Artificial Intelligence (AAAI'14)
Conference date
07-2014
Conference city
Québec
Conference country
Canada
Book title
AAAI'14 Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence
Author
Brodley, Carla E.; Stone, Peter
Publisher
AAAI Press
Publisher city
Palo Alto (USA)
Year
2014
Pages number
3155
ISBN
978-1-57735-661-5
URI
https://basepub.dauphine.fr/handle/123456789/16452
Collections
  • LAMSADE : Publications
Metadata
Show full item record
Author
Goldsmith, Judy
142492 University of Kentucky
Lang, Jérôme
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Mattei, Nicholas
status unknown
Perny, Patrice
233 Laboratoire d'Informatique de Paris 6 [LIP6]
Type
Communication / Conférence
Item number of pages
698-704
Abstract (EN)
Positional scoring rules in voting compute the score of an alternative by summing the scores for the alternative induced by every vote. This summation principle ensures that all votes contribute equally to the score of an alternative. We relax this assumption and, instead, aggregate scores by taking into account the rank of a score in the ordered list of scores obtained from the votes. This defines a new family of voting rules, rank-dependent scoring rules (RDSRs), based on ordered weighted average (OWA) operators, which, include all scoring rules, and many others, most of which of new. We study some properties of these rules, and show, empirically, that certain RDSRs are less manipulable than Borda voting, across a variety of statistical cultures.

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