
Portioning Using Ordinal Preferences: Fairness and Efficiency
Airiau, Stéphane; Aziz, Haris; Caragiannis, Ioannis; Lang, Jérôme; Peters, Dominik; Kruger, Justin (2019), Portioning Using Ordinal Preferences: Fairness and Efficiency, in Sarit Kraus, Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, IJCAI, p. 11-17. 10.24963/ijcai.2019/2
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Type
Communication / ConférenceDate
2019Conference title
28th International Joint Conference on Artificial Intelligence (IJCAI 2019)Conference date
2019Conference country
CHINABook title
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019Book author
Sarit KrausPublisher
IJCAI
ISBN
978-0-9992411-4-1
Pages
11-17
Publication identifier
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Show full item recordAuthor(s)
Airiau, Stéphane
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Aziz, Haris
Caragiannis, Ioannis
Lang, Jérôme
Peters, Dominik
Kruger, Justin
Abstract (EN)
A public divisible resource is to be divided among projects. We study rules that decide on a distribution of the budget when voters have ordinal preference rankings over projects. Examples of such portioning problems are participatory budgeting, time shares, and parliament elections. We introduce a family of rules for portioning, inspired by positional scoring rules. Rules in this family are given by a scoring vector (such as plurality or Borda) associating a positive value with each rank in a vote, and an aggregation function such as leximin or the Nash product. Our family contains well-studied rules, but most are new. We discuss computational and normative properties of our rules. We focus on fairness, and introduce the SD-core, a group fairness notion. Our Nash rules are in the SD-core, and the leximin rules satisfy individual fairness properties. Both are Pareto-efficient.Subjects / Keywords
Agent-based and Multi-agent Systems; Cooperative Games; Computational Social ChoiceRelated items
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