Weighted envy-freeness for submodular valuations

Luisa Montanari, Ulrike Schmidt-Kraepelin, Warut Suksompong () and Nicholas Teh
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Luisa Montanari: Technische Universität Berlin
Ulrike Schmidt-Kraepelin: TU Eindhoven
Warut Suksompong: National University of Singapore
Nicholas Teh: University of Oxford

Social Choice and Welfare, 2025, vol. 65, issue 4, No 8, 983-1016

Abstract: Abstract We investigate the fair allocation of indivisible goods to agents with possibly different entitlements represented by weights. Previous work has shown that guarantees for additive valuations with existing envy-based notions cannot be extended to the case where agents have matroid-rank (i.e., binary submodular) valuations. We propose two families of envy-based notions for matroid-rank and general submodular valuations, one based on the idea of transferability and the other on marginal values. We show that our notions can be satisfied via generalizations of rules such as picking sequences and maximum weighted Nash welfare. In addition, we introduce welfare measures based on harmonic numbers, and show that variants of maximum weighted harmonic welfare offer stronger fairness guarantees than maximum weighted Nash welfare under matroid-rank valuations.

Date: 2025
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DOI: 10.1007/s00355-025-01599-6

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