Strategy-Proof House Allocation with Existing Tenants over Social Networks

Bo You, Ludwig Dierks, Taiki Todo, Minming Li, Makoto Yokoo

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

1 Citation (Scopus)

Abstract

Mechanism design over social networks, whose goal is to incentivize agents to diffuse the information of a mechanism to their followers, as well as to report their true preferences, is one of the new trends in market design. In this paper, we reconsider the traditional house allocation problem with existing tenants from the perspective of mechanism design over social networks. Since our model is a generalization of the networked housing market investigated by Kawasaki et al. [9], no mechanism simultaneously satisfies strategy-proofness, individual rationality and Pareto efficiency for general social network structures. We therefore examine the cases where the social network has a tree structure. We first show that even for the restricted structure, a weaker welfare requirement called non-wastefulness is not achievable by any strategy-proof and individually rational mechanism. We then show that a non-trivial modification of You Request My House - I Get Your Turn mechanism (YRMH-IGYT) is individually rational, strategy-proof, and weakly non-wasteful. Furthermore, it chooses an allocation in the strict core for neighbors and satisfies weak group strategy-proofness.

Original languageEnglish
Title of host publicationInternational Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1446-1454
Number of pages9
ISBN (Electronic)9781713854333
Publication statusPublished - 2022
Event21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022 - Auckland, Virtual, New Zealand
Duration: May 9 2022May 13 2022

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume3
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

Conference21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022
Country/TerritoryNew Zealand
CityAuckland, Virtual
Period5/9/225/13/22

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

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