Abstract
In fair division of indivisible goods, ℓ-out-of-d maximin share (MMS) is the value that an agent can guarantee by partitioning the goods into d bundles and choosing the ℓ least preferred bundles. Most existing works aim to guarantee to all agents a constant fraction of their 1-out-of-n MMS. But this guarantee is sensitive to small perturbation in agents' cardinal valuations. We consider a more robust approximation notion, which depends only on the agents' ordinal rankings of bundles. We prove the existence of ℓ-out-of-(Equation presented) MMS allocations of goods for any integer ℓ ≥ 1, and present a polynomial-time algorithm that finds a 1-out-of-(Equation presented) MMS allocation when ℓ = 1. We further develop an algorithm that provides a weaker ordinal approximation to MMS for any ℓ > 1.
Original language | English |
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Title of host publication | Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023 |
Editors | Edith Elkind |
Publisher | International Joint Conferences on Artificial Intelligence |
Pages | 6894-6899 |
Number of pages | 6 |
ISBN (Electronic) | 9781956792034 |
DOIs | |
State | Published - 2023 |
Externally published | Yes |
Event | 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023 - Macao, China Duration: 19 Aug 2023 → 25 Aug 2023 |
Publication series
Name | IJCAI International Joint Conference on Artificial Intelligence |
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Volume | 2023-August |
ISSN (Print) | 1045-0823 |
Conference
Conference | 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023 |
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Country/Territory | China |
City | Macao |
Period | 19/08/23 → 25/08/23 |
Bibliographical note
Publisher Copyright:© 2023 International Joint Conferences on Artificial Intelligence. All rights reserved.