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Journal Articles Journal of Artificial Intelligence Research Year : 2022

Fair in the Eyes of Others

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Aurélie Beynier
Nicolas Maudet

Abstract

Envy-freeness is a widely studied notion in resource allocation, capturing some aspects of fairness. The notion of envy being inherently subjective though, it might be the case that an agent envies another agent, but that from the other agents' point of view, she has no reason to do so. The difficulty here is to define the notion of objectivity, since no ground-truth can properly serve as a basis of this definition. A natural approach is to consider the judgement of the other agents as a proxy for objectivity. Building on previous work by Parijs (who introduced "unanimous envy") we propose the notion of approval envy: an agent ai experiences approval envy towards aj if she is envious of aj, and sufficiently many agents agree that this should be the case, from their own perspectives. Another thoroughly studied notion in resource allocation is proportionality. The same variant can be studied, opening natural questions regarding the links between these two notions. We exhibit several properties of these notions. Computing the minimal threshold guaranteeing approval envy and approval non-proportionality clearly inherits well-known intractable results from envy-freeness and proportionality, but (i) we identify some tractable cases such as house allocation; and (ii) we provide a general method based on a mixed integer programming encoding of the problem, which proves to be efficient in practice. This allows us in particular to show experimentally that existence of such allocations, with a rather small threshold, is very often observed.
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Dates and versions

hal-03863934 , version 1 (21-11-2022)

Identifiers

Cite

Parham Shams, Aurélie Beynier, Sylvain Bouveret, Nicolas Maudet. Fair in the Eyes of Others. Journal of Artificial Intelligence Research, 2022, 75, pp.913-951. ⟨10.1613/jair.1.13778⟩. ⟨hal-03863934⟩
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