Fair and Truthful Mechanisms for Dichotomous Valuations
Moshe Babaioff, Tomer Ezra, Uriel Feige
Abstract
We consider the problem of allocating a set on indivisible items to agents with private preferences in an efficient and fair way. We focus on valuations that have dichotomous marginals, in which the added value of any item to a set is either 0 or 1, and aim to design truthful allocation mechanisms (without money) that maximize welfare and are fair. For the case that agents have submodular valuations with dichotomous marginals, we design such a deterministic truthful allocation mechanism. The allocation output by our mechanism is Lorenz dominating, and consequently satisfies many desired fairness properties, such as being envy-free up to any item (EFX), and maximizing the Nash Social Welfare (NSW). We then show that our mechanism with random priorities is envy-free ex-ante, while having all the above properties ex-post. Furthermore, we present several impossibility results precluding similar results for the larger class of XOS valuations. To gauge the robustness of our positive results, we also study ǫ-dichotomous valuations, in which the added value of any item to a set is either non-positive, or in the range [1, 1 + ǫ]. We show several impossibility results in this setting, and also a positive result: for agents that have additive ǫ-dichotomous valuations with sufficiently small ǫ, we design a randomized truthful mechanism with strong ex-post guarantees. For ρ = 1 1+ǫ , the allocations that it produces generate at least a ρ-fraction of the maximum welfare, and enjoy ρ-approximations for various fairness properties, such as being envy-free up to one item (EF1), and giving each agent at least her maximin share.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers19
- Fair and Efficient Allocations of Chores under Bivalued PreferencesJugal Garg, Aniket Murhekar, John QinAAAI 2022 · 63 citations
- On Fair Division under Heterogeneous Matroid ConstraintsAmitay Dror, Michal Feldman, Erel Segal-HaleviAAAI 2021 · 42 citations
- Fair and Efficient Allocations Without Obvious ManipulationsAlexandros Psomas, Paritosh VermaNeurIPS 2022 · 37 citations
- Truthful and Fair Mechanisms for Matroid-Rank ValuationsSiddharth Barman, Paritosh VermaAAAI 2022 · 31 citations
- Maximizing Nash Social Welfare in 2-Value InstancesHannaneh Akrami, Bhaskar Ray Chaudhury, Martin Hoefer, Kurt Mehlhorn et al.AAAI 2022 · 31 citations
Builds on1
Related papers
- Truthful and Almost Envy-Free Mechanism of Allocating Indivisible Goods: the Power of RandomnessXiaolin Bu, Biaoshuai TaoFOCS 2025 · 14 citations
- Fair and Efficient Allocations under Subadditive ValuationsBhaskar Ray Chaudhury, Jugal Garg, Ruta MehtaAAAI 2021 · 41 citations
- Randomized and Deterministic Maximin-share Approximations for Fractionally Subadditive ValuationsHannaneh Akrami, Kurt Mehlhorn, Masoud Seddighin, Golnoosh ShahkaramiNeurIPS 2023 · 27 citations
- Approximating Nash Social Welfare by Matching and Local SearchJugal Garg, Edin Husic, Wenzheng Li, László A. Végh et al.STOC 2023 · 8 citations
- Approximating Nash Social Welfare under Submodular Valuations through (Un)MatchingsJugal Garg, Pooja Kulkarni, Rucha KulkarniSODA 2020 · 39 citations
