Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/108447
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dc.contributorDepartment of Computing-
dc.creatorAmanatidis, Gen_US
dc.creatorAziz, Hen_US
dc.creatorBirmpas, Gen_US
dc.creatorFilos-Ratsikas, Aen_US
dc.creatorLi, Ben_US
dc.creatorMoulin, Hen_US
dc.creatorVoudouris, AAen_US
dc.creatorWu, Xen_US
dc.date.accessioned2024-08-19T01:58:28Z-
dc.date.available2024-08-19T01:58:28Z-
dc.identifier.issn0004-3702en_US
dc.identifier.urihttp://hdl.handle.net/10397/108447-
dc.language.isoenen_US
dc.publisherElsevier BVen_US
dc.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/).en_US
dc.rightsThe 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.en_US
dc.subjectDiscrete fair divisionen_US
dc.subjectEF1en_US
dc.subjectEFXen_US
dc.subjectEnvy-freenessen_US
dc.subjectMMSen_US
dc.subjectProportionalityen_US
dc.titleFair division of indivisible goods : recent progress and open questionsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume322en_US
dc.identifier.doi10.1016/j.artint.2023.103965en_US
dcterms.abstractAllocating 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.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationArtificial intelligence, Sept 2023, v. 322, 103965en_US
dcterms.isPartOfArtificial intelligenceen_US
dcterms.issued2023-09-
dc.identifier.scopus2-s2.0-85162904937-
dc.identifier.eissn1872-7921en_US
dc.identifier.artn103965en_US
dc.description.validate202408 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis work is partially supported by the ERC Advanced Grant 788893 AMDROMA “Algorithmic and Mechanism Design Research in Online Markets”, the MIUR PRIN project ALGADIMAR “Algorithms, Games, Digital Markets”, the NWO Veni project No. VI.Veni.192.153, NSFC No. 62102333, HKSAR RGC No. PolyU 25211321, PolyU Start-up No. P0034420, FDCT (File no. 0014/2022/AFJ, 0085/2022/A, 0143/2020/A3, SKL-IOTSC-2021-2023).en_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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