Fair division of indivisible goods: Recent progress and open questions

Georgios Amanatidis, Haris Aziz, Georgios Birmpas, Aris Filos-Ratsikas, Bo Li, Herve Moulin, Alexandros A. Voudouris, Xiaowei Wu

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Allocating resources to individuals in a fair manner has been a topic of interest since ancient times, with most of the early mathematical work on the problem focusing on resources that are infinitely divisible. Over the last decade, there has been a surge of papers studying computational questions regarding the indivisible case, for which exact fairness notions such as envy-freeness and proportionality are hard to satisfy. One main theme in the recent research agenda is to investigate the extent to which their relaxations, like maximin share fairness (MMS) and envy-freeness up to any good (EFX), can be achieved. In this survey, we present a comprehensive review of the recent progress made in the related literature by highlighting different ways to relax fairness notions, common algorithm design techniques, and the most interesting questions for future research.
Original languageEnglish
Article number103965
Pages (from-to)1-25
JournalArtificial Intelligence
Volume322
Issue numberSeptember 2023
Early online date16 Jun 2023
DOIs
Publication statusPublished - 26 Jun 2023

Keywords / Materials (for Non-textual outputs)

  • discrete fair division
  • envy-freeness
  • proprtionality
  • EF1
  • EFX
  • MMS

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