On Truthful Mechanisms for Maximin Share Allocations
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Abstract (arXiv)
We study a fair division problem with indivisible items, namely the computation of maximin share allocations. Given a set of n players, the maximin share of a single player is the best she can guarantee to herself, if she would partition the items in any way she prefers, into n bundles, and then receive her least desirable bundle. The objective then is to find an allocation, so that each player is guaranteed her maximin share. Previous works have studied this problem mostly algorithmically, providing constant factor approximation algorithms. In this work we embark on a mechanism design approach and investigate the existence of truthful mechanisms. We propose three models regarding the information that the mechanism attempts to elicit from the players, based on the cardinal and ordinal representation of preferences. We establish positive and negative (impossibility) results for each model and highlight the limitations imposed by truthfulness on the approximability of the problem. Finally, we pay particular attention to the case of two players, which already leads to challenging questions.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 May 2016.
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Citing papers per year: 2021: 3; 2022: 1; 2023: 1; 2024: 1.
6 papers.
- 2021Fair and Efficient Resource Allocation with Partial Informationcited by 3
- 2021Allocating Indivisible Goods to Strategic Agents: Pure Nash Equilibria and Fairnesscited by 3
- 2021Egalitarian Judgment Aggregationcited by 2
- 2022Fair Shares: Feasibility, Domination and Incentivescited by 2
- 2024Fair Allocation in Dynamic Mechanism Designcited by 1
- 2023Constrained Serial Dictatorships can be Faircited by 0
- 2024Fair Allocation in Dynamic Mechanism Design31 May 2024
- 2023Constrained Serial Dictatorships can be Fair11 Jan 2023
- 2022Fair Shares: Feasibility, Domination and Incentives16 May 2022
- 2021Allocating Indivisible Goods to Strategic Agents: Pure Nash Equilibria and Fairness17 Sep 2021
- 2021Fair and Efficient Resource Allocation with Partial Information20 May 2021
- 2021Egalitarian Judgment Aggregation4 Feb 2021