TY - GEN
T1 - Controlled school choice with soft bounds and overlapping types
AU - Kurata, Ryoji
AU - Goto, Masahiro
AU - Iwasaki, Atsushi
AU - Yokoo, Makoto
N1 - Publisher Copyright:
Copyright © 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2015/6/1
Y1 - 2015/6/1
N2 - School choice programs are implemented to give students/parents an opportunity to choose the public school the students attend. Controlled school choice programs need to provide choices for students/parents while maintaining distributional constraints on the balance on the composition of students, typically in terms of socioeconomic status. Previous works show that setting soft-bounds, which flexibly change the priorities of students based on their types, is more appropriate than setting hard-bounds, which strictly limit the number of accepted students for each type. We consider a case where soft-bounds are imposed and one student can belong to multiple types, e.g., "financially-distressed" and "minority" types. We first show that when we apply a model that is a straightforward extension of an existing model for disjoint types, there is a chance that no stable matching exists. Thus, we propose an alternative model and an alternative stability definition, where a school has reserved seats for each type. We show that a stable matching is guaranteed to exist in this model, and develop a mechanism called Deferred Acceptance for Overlapping Types (DA-OT). The DA-OT mechanism is strategy-proof and obtains the student-optimal matching within all stable matchings. Computer simulation results illustrate that the DA-OT outperforms an artificial cap mechanism, where the number of seats for each type is fixed.
AB - School choice programs are implemented to give students/parents an opportunity to choose the public school the students attend. Controlled school choice programs need to provide choices for students/parents while maintaining distributional constraints on the balance on the composition of students, typically in terms of socioeconomic status. Previous works show that setting soft-bounds, which flexibly change the priorities of students based on their types, is more appropriate than setting hard-bounds, which strictly limit the number of accepted students for each type. We consider a case where soft-bounds are imposed and one student can belong to multiple types, e.g., "financially-distressed" and "minority" types. We first show that when we apply a model that is a straightforward extension of an existing model for disjoint types, there is a chance that no stable matching exists. Thus, we propose an alternative model and an alternative stability definition, where a school has reserved seats for each type. We show that a stable matching is guaranteed to exist in this model, and develop a mechanism called Deferred Acceptance for Overlapping Types (DA-OT). The DA-OT mechanism is strategy-proof and obtains the student-optimal matching within all stable matchings. Computer simulation results illustrate that the DA-OT outperforms an artificial cap mechanism, where the number of seats for each type is fixed.
UR - http://www.scopus.com/inward/record.url?scp=84959917439&partnerID=8YFLogxK
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M3 - Conference contribution
AN - SCOPUS:84959917439
T3 - Proceedings of the National Conference on Artificial Intelligence
SP - 951
EP - 957
BT - Proceedings of the 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015
PB - AI Access Foundation
T2 - 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015
Y2 - 25 January 2015 through 30 January 2015
ER -