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Voting with Rank Dependent Scoring Rules

Goldsmith, Judy; Lang, Jérôme; Mattei, Nicholas; Perny, Patrice (2014), Voting with Rank Dependent Scoring Rules, in Brodley, Carla E.; Stone, Peter, AAAI'14 Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, AAAI Press : Palo Alto (USA), p. 698-704

Type
Communication / Conférence
External document link
http://www.aaai.org/ocs/index.php/AAAI/AAAI14/paper/view/8549
Date
2014
Conference title
28th AAAI Conference on Artificial Intelligence (AAAI'14)
Conference date
2014-07
Conference city
Québec
Conference country
Canada
Book title
AAAI'14 Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence
Book author
Brodley, Carla E.; Stone, Peter
Publisher
AAAI Press
Published in
Palo Alto (USA)
ISBN
978-1-57735-661-5
Number of pages
3155
Pages
698-704
Metadata
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Author(s)
Goldsmith, Judy
University of Kentucky
Lang, Jérôme
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Mattei, Nicholas

Perny, Patrice
Laboratoire d'Informatique de Paris 6 [LIP6]
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.
Subjects / Keywords
social choice; voting