Envy-Free House Allocation under Uncertain Preferences
Haris Aziz, Isaiah Iliffe, Bo Li, Angus Ritossa, Ankang Sun, Mashbat Suzuki
Abstract
Envy-freeness is one of the most important fairness concerns when allocating resources. We study the envy-free house allocation problem when agents have uncertain preferences over items and consider several well-studied preference uncertainty models. The central problem that we focus on is computing an allocation that has the highest probability of being envyfree. We show that each model leads to a distinct set of algorithmic and complexity results, including detailed results on (in-)approximability. En route, we consider two related problems of checking whether there exists an allocation that is possibly or necessarily envy-free. We give a complete picture of the computational complexity of these two problems for all the uncertainty models we consider.
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