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Guaranteeing Maximin Shares: Some Agents Left Behind

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  • Hadi Hosseini
  • Andrew Searns

Abstract

The maximin share (MMS) guarantee is a desirable fairness notion for allocating indivisible goods. While MMS allocations do not always exist, several approximation techniques have been developed to ensure that all agents receive a fraction of their maximin share. We focus on an alternative approximation notion, based on the population of agents, that seeks to guarantee MMS for a fraction of agents. We show that no optimal approximation algorithm can satisfy more than a constant number of agents, and discuss the existence and computation of MMS for all but one agent and its relation to approximate MMS guarantees. We then prove the existence of allocations that guarantee MMS for $\frac{2}{3}$ of agents, and devise a polynomial time algorithm that achieves this bound for up to nine agents. A key implication of our result is the existence of allocations that guarantee $\text{MMS}^{\lceil{3n/2}\rceil}$, i.e., the value that agents receive by partitioning the goods into $\lceil{\frac{3}{2}n}\rceil$ bundles, improving the best known guarantee of $\text{MMS}^{2n-2}$. Finally, we provide empirical experiments using synthetic data.

Suggested Citation

  • Hadi Hosseini & Andrew Searns, 2021. "Guaranteeing Maximin Shares: Some Agents Left Behind," Papers 2105.09383, arXiv.org.
  • Handle: RePEc:arx:papers:2105.09383
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    References listed on IDEAS

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    1. Ortega, Josué, 2018. "Social integration in two-sided matching markets," Journal of Mathematical Economics, Elsevier, vol. 78(C), pages 119-126.
    2. Feldman, Allan M & Kirman, Alan, 1974. "Fairness and Envy," American Economic Review, American Economic Association, vol. 64(6), pages 995-1005, December.
    3. Eric Budish, 2011. "The Combinatorial Assignment Problem: Approximate Competitive Equilibrium from Equal Incomes," Journal of Political Economy, University of Chicago Press, vol. 119(6), pages 1061-1103.
    4. Ioannis Caragiannis & David Kurokawa & Herve Moulin & Ariel D. Procaccia & Nisarg Shah & Junxing Wang, 2016. "The Unreasonable Fairness of Maximum Nash Welfare," Working Papers 2016_08, Business School - Economics, University of Glasgow.
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    Cited by:

    1. Hadi Hosseini & Sujoy Sikdar & Rohit Vaish & Lirong Xia, 2022. "Fairly Dividing Mixtures of Goods and Chores under Lexicographic Preferences," Papers 2203.07279, arXiv.org.
    2. Hadi Hosseini & Zhiyi Huang & Ayumi Igarashi & Nisarg Shah, 2022. "Class Fairness in Online Matching," Papers 2203.03751, arXiv.org.

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