Fair Allocation with Initial Utilities
Niclas Boehmer, Luca Kreisel

TL;DR
This paper explores fair allocation of indivisible resources considering agents' initial utilities, introducing new fairness notions and algorithms to ensure equitable outcomes despite initial inequalities.
Contribution
It extends the classic resource allocation model by incorporating initial utilities and proposes a new fairness concept, minimum-EF1-init, with a polynomial-time algorithm for its computation.
Findings
Complete EF1-like allocations may not exist with initial utilities.
Finding EF1-like allocations is computationally hard in this setting.
The proposed minimum-EF1-init algorithm guarantees fair allocations in polynomial time.
Abstract
The problem of allocating indivisible resources to agents arises in a wide range of domains, including treatment distribution and social support programs. An important goal in algorithm design for this problem is fairness, where the focus in previous work has been on ensuring that the computed allocation provides equal treatment to everyone. However, this perspective disregards that agents may start from unequal initial positions, which is crucial to consider in settings where fairness is understood as equality of outcome. In such settings, the goal is to create an equal final outcome for everyone by leveling initial inequalities through the allocated resources. To close this gap, focusing on agents with additive utilities, we extend the classic model by assigning each agent an initial utility and study the existence and computational complexity of several new fairness notions following…
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Taxonomy
TopicsGame Theory and Voting Systems · Auction Theory and Applications · Ethics and Social Impacts of AI
