TY - GEN
T1 - Game theoretic analysis for two-sided matching with resource allocation
AU - Yahiro, Kentaro
AU - Yokoo, Makoto
N1 - Funding Information:
This work is partially supported by JSPS KAKENHI Grant JP17H00761 and JST SICORP JPMJSC1607.
PY - 2020
Y1 - 2020
N2 - In this work, we consider a student-project-resource matching-allocation problem, where students have preferences over projects and the projects have preferences over students. Although students are many-to-one matched to projects, indivisible resources are many-to-one allocated to projects whose capacities are endogenously determined by the resources allocated to them. Traditionally, this problem is decomposed into two separate problems: (1) resources are allocated to projects based on expectations (resource allocation problem), and (2) students are matched to projects based on the capacities determined in the previous problem (matching problem). Although both problems are well-understood, if the expectations used in the first are incorrect, we obtain a suboptimal outcome. Thus, this problem must be solved as a whole without dividing it in two parts. We show that no strategyproof mechanism satisfies fairness (i.e., no student has justified envy) and weak efficiency requirements on students' welfare. Given this impossibility result, we develop a new strategyproof mechanism that strikes a good balance between fairness and efficiency and assess it by experiments.
AB - In this work, we consider a student-project-resource matching-allocation problem, where students have preferences over projects and the projects have preferences over students. Although students are many-to-one matched to projects, indivisible resources are many-to-one allocated to projects whose capacities are endogenously determined by the resources allocated to them. Traditionally, this problem is decomposed into two separate problems: (1) resources are allocated to projects based on expectations (resource allocation problem), and (2) students are matched to projects based on the capacities determined in the previous problem (matching problem). Although both problems are well-understood, if the expectations used in the first are incorrect, we obtain a suboptimal outcome. Thus, this problem must be solved as a whole without dividing it in two parts. We show that no strategyproof mechanism satisfies fairness (i.e., no student has justified envy) and weak efficiency requirements on students' welfare. Given this impossibility result, we develop a new strategyproof mechanism that strikes a good balance between fairness and efficiency and assess it by experiments.
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M3 - Conference contribution
AN - SCOPUS:85096692265
T3 - Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
SP - 1548
EP - 1556
BT - Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020
A2 - An, Bo
A2 - El Fallah Seghrouchni, Amal
A2 - Sukthankar, Gita
PB - International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
T2 - 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020
Y2 - 19 May 2020
ER -