Mechanism Design for School Choice with Soft Diversity Constraints
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Main track. Pages 153-159. https://doi.org/10.24963/ijcai.2020/22
We study the controlled school choice problem where students may belong to overlapping types and schools have soft target quotas for each type. We formalize fairness concepts for the setting that extend fairness concepts considered for restricted settings without overlapping types. Our central contribution is presenting a new class of algorithms that takes into account the representations of combinations of student types. The algorithms return matchings that are non-wasteful and satisfy fairness for same types. We further prove that the algorithms are strategyproof for the students and yield a fair outcome with respect to the induced quotas for type combinations. We experimentally compare our algorithms with two existing approaches in terms of achieving diversity goals and satisfying fairness.
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