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Envy-Free and Efficient Allocations for Graphical Valuations

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Algorithmic Decision Theory (ADT 2024)

Abstract

We consider the complexity of finding envy-free allocations for the class of graphical valuations. Graphical valuations were introduced by Christodoulou et al. [14] as a structured class of valuations that admit allocations that are envy-free up to any item(EFX). These are valuations where every item is valued by two agents, lending a (simple) graph structure to the utilities, where the agents are vertices and are adjacent if and only if they value a (unique) common item. Finding envy-free allocations for general valuations is known to be computationally intractable even for very special cases: in particular, even for binary valuations, and even for identical valuations with two agents. We show that, for binary graphical valuations, the existence of envy-free allocations can be determined in polynomial time. In contrast, we also show that allowing for even slightly more general utilities \(\{0,1,d\}\) leads to intractability even for graphical valuations. This motivates other approaches to tractability, and to that end, we exhibit the fixed-parameter tractability of the problem parameterized by the vertex cover number of the graph when the number of distinct utilities is bounded. We also show that, all graphical instances that admit EF allocations also admit one that is non-wasteful. Since EFX allocations are possibly wasteful, we also address the question of determining the price of fairness of EFX allocations. We show that the price of EFX with respect to utilitarian welfare is one for binary utilities, but can be arbitrarily large \(\{0, 1, d\}\) valuations. We also show the hardness of deciding the existence of an EFX allocation which is also welfare-maximizing and of finding a welfare-maximizing allocation within the set of EFX allocations.

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Notes

  1. 1.

    We refer the reader to next section for the definition of EFX.

  2. 2.

    An algorithm that runs in time f(k)poly(nm) where f is some computable function of the parameter k.

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Correspondence to Aditi Sethia .

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Misra, N., Sethia, A. (2025). Envy-Free and Efficient Allocations for Graphical Valuations. In: Freeman, R., Mattei, N. (eds) Algorithmic Decision Theory. ADT 2024. Lecture Notes in Computer Science(), vol 15248. Springer, Cham. https://doi.org/10.1007/978-3-031-73903-3_17

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  • DOI: https://doi.org/10.1007/978-3-031-73903-3_17

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