Web: http://arxiv.org/abs/2201.10053

Jan. 26, 2022, 2:11 a.m. | Aida Rahmattalabi, Phebe Vayanos, Kathryn Dullerud, Eric Rice

cs.LG updates on arXiv.org arxiv.org

We study the problem of learning, from observational data, fair and
interpretable policies that effectively match heterogeneous individuals to
scarce resources of different types. We model this problem as a multi-class
multi-server queuing system where both individuals and resources arrive
stochastically over time. Each individual, upon arrival, is assigned to a queue
where they wait to be matched to a resource. The resources are assigned in a
first come first served (FCFS) fashion according to an eligibility structure
that encodes …

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