Efficient allocation mechanism with endowments and distributional constraints

Takamasa Suzuki, Akihisa Tamura, Makoto Yokoo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

We consider an allocation problem of multiple types objects to agents, where each type of an object has multiple copies (e.g., mult iple seats of a school), each agent is endowed with an object, and some distributional constraints are imposed on the allocation (e.g., minimum/maximum quotas). We develop a mechanism that is based on the Top Trading Cycles mechanism, which Is strategy-proof, feasible (always satisfies distributional constraints). Pareto efficient, and individually rational, assuming the distributional constraints are represented as an M-convex set. The class of distributional cons traints we consider contains many situations raised from realistic matching problems, including individual minimum/maximum quot as, regional maximum quotas, type-specific quotas, and distance constraints. To the best of our knowledge, we are the first to develop a mechanism with these desirable properties.

Original languageEnglish
Title of host publication17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages50-67
Number of pages18
ISBN (Print)9781510868083
Publication statusPublished - 2018
Event17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018 - Stockholm, Sweden
Duration: Jul 10 2018Jul 15 2018

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume1
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Other

Other17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018
Country/TerritorySweden
CityStockholm
Period7/10/187/15/18

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

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