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Learning Optimal and Fair Policies for Online Allocation of Scarce Societal Resources from Data Collected in Deployment
We study the problem of allocating scarce societal resources of different types (e. g., permanent housing, deceased donor kidneys for transplantation, ventilators) to heterogeneous allocatees on a waitlist (e. g., people experiencing homelessness, individuals suffering from end-stage renal disease, Covid-19 patients) based on their observed covariates.
Fairness in Contextual Resource Allocation Systems: Metrics and Incompatibility Results
We study critical systems that allocate scarce resources to satisfy basic needs, such as homeless services that provide housing.
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