Game theoretic analysis for two-sided matching with resource allocation

Kentaro Yahiro, Makoto Yokoo

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

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.

本文言語英語
ホスト出版物のタイトルProceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020
編集者Bo An, Amal El Fallah Seghrouchni, Gita Sukthankar
出版社International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
ページ1548-1556
ページ数9
ISBN(電子版)9781450375184
出版ステータス出版済み - 2020
イベント19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020 - Virtual, Auckland, ニュージ―ランド
継続期間: 5 19 2020 → …

出版物シリーズ

名前Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
2020-May
ISSN(印刷版)1548-8403
ISSN(電子版)1558-2914

会議

会議19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020
Countryニュージ―ランド
CityVirtual, Auckland
Period5/19/20 → …

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

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