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Fair Division Minimizing Inequality

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Progress in Artificial Intelligence (EPIA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11805))

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Abstract

Behavioural economists have shown that people are often averse to inequality and will make choices to avoid unequal outcomes. In this paper, we consider how to allocate indivisible goods fairly to agents with additive utilities, so as to minimize inequality. We consider how this interacts with axiomatic properties such as envy-freeness, Pareto efficiency and strategy-proofness. We also consider the computational complexity of computing allocations minimizing inequality. Unfortunately, this is computationally intractable in general so we consider several tractable mechanisms that minimize greedily the inequality. Finally, we run experiments to explore the performance of these mechanisms.

Funded by the European Research Council under the Horizon 2020 Programme via AMPLify 670077.

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Authors and Affiliations

  1. Technical University, Berlin, Germany

    Martin Aleksandrov & Toby Walsh

  2. Chinese Academy of Sciences, Beijing, China

    Cunjing Ge

Authors
  1. Martin Aleksandrov
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  2. Cunjing Ge
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  3. Toby Walsh
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Corresponding author

Correspondence to Martin Aleksandrov .

Editor information

Editors and Affiliations

  1. INESC-TEC, University of Trás-os-Montes and Alto Douro, Vila Real, Portugal

    Paulo Moura Oliveira

  2. University of Minho, Braga, Portugal

    Paulo Novais

  3. LIACC/UP, University of Porto, Porto, Portugal

    Luís Paulo Reis

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Aleksandrov, M., Ge, C., Walsh, T. (2019). Fair Division Minimizing Inequality. In: Moura Oliveira, P., Novais, P., Reis, L. (eds) Progress in Artificial Intelligence. EPIA 2019. Lecture Notes in Computer Science(), vol 11805. Springer, Cham. https://doi.org/10.1007/978-3-030-30244-3_49

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  • DOI: https://doi.org/10.1007/978-3-030-30244-3_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-30243-6

  • Online ISBN: 978-3-030-30244-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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