Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/108447
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Title: Fair division of indivisible goods : recent progress and open questions
Authors: Amanatidis, G
Aziz, H
Birmpas, G
Filos-Ratsikas, A
Li, B 
Moulin, H
Voudouris, AA
Wu, X
Issue Date: Sep-2023
Source: Artificial intelligence, Sept 2023, v. 322, 103965
Abstract: 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.
Keywords: Discrete fair division
EF1
EFX
Envy-freeness
MMS
Proportionality
Publisher: Elsevier BV
Journal: Artificial intelligence 
ISSN: 0004-3702
EISSN: 1872-7921
DOI: 10.1016/j.artint.2023.103965
Rights: © 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
The following publication Amanatidis, G., Aziz, H., Birmpas, G., Filos-Ratsikas, A., Li, B., Moulin, H., Voudouris, A. A., & Wu, X. (2023). Fair division of indivisible goods: Recent progress and open questions. Artificial Intelligence, 322, 103965 is available at https://doi.org/10.1016/j.artint.2023.103965.
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