Portioning Using Ordinal Preferences: Fairness and Efficiency
Portioning Using Ordinal Preferences: Fairness and Efficiency
Stéphane Airiau, Haris Aziz, Ioannis Caragiannis, Justin Kruger, Jérôme Lang, Dominik Peters
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence
Main track. Pages 11-17.
https://doi.org/10.24963/ijcai.2019/2
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.
Keywords:
Agent-based and Multi-agent Systems: Cooperative Games
Agent-based and Multi-agent Systems: Computational Social Choice