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Conference Papers Year : 2018

Knowledge, Fairness, and Social Constraints

Abstract

In the context of fair allocation of indivisible items, fairness concepts often compare the satisfaction of an agent to the satisfaction she would have from items that are not allocated to her: in particular, envy-freeness requires that no agent prefers the share of someone else to her own share. We argue that these notions could also be defined relative to the knowledge that an agent has on how the items that she does not receive are distributed among other agents. We define a family of epistemic notions of envy-freeness, parameterized by a social graph, where an agent observes the share of her neighbours but not of her non-neighbours. We also define an intermediate notion between envy-freeness and proportionality, also parameterized by a social graph. These weaker notions of envy-freeness are useful when seeking a fair allocation, since envy-freeness is often too strong. We position these notions with respect to known ones, thus revealing new rich hierarchies of fairness concepts. Finally, we present a very general framework that covers all the existing and many new fairness concepts.
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Dates and versions

hal-02171232 , version 1 (02-07-2019)

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  • HAL Id : hal-02171232 , version 1

Cite

Haris Aziz, Sylvain Bouveret, Ioannis Caragiannis, Ira Giagkousi, Jérôme Lang. Knowledge, Fairness, and Social Constraints. 32nd AAAI Conference on Artificial Intelligence (AAAI-18), Feb 2018, New Orleans, Louisiana, United States. pp.4638-4645. ⟨hal-02171232⟩
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