Decentralized marriage models

Kshitija Taywade, Judy Goldsmith, Brent Harrison

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Most matching algorithms are centralized in that a single agent determines how other agents are matched together. This is contrary to how humans form matches in the real world. We propose three decentralized approaches for finding matchings that are inspired by three techniques that humans use to find matches: a grid environment, with agents wandering around, interacting and deciding preferences over potential partners; affiliation networks where agencies recommend potential partners; and small-world social networks, where individuals are probabilistically introduced to one another by friends. We introduce a heuristic algorithm that can be used in each of these environments. We also explore how this algorithm can scale to a large number of agents.

Original languageEnglish
Title of host publicationProceedings of the 33rd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2020
EditorsEric Bell, Roman Bartak
Pages213-216
Number of pages4
ISBN (Electronic)9781577358213
StatePublished - 2020
Event33rd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2020 - North Miami Beach, United States
Duration: May 17 2020May 20 2020

Publication series

NameProceedings of the 33rd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2020

Conference

Conference33rd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2020
Country/TerritoryUnited States
CityNorth Miami Beach
Period5/17/205/20/20

Bibliographical note

Publisher Copyright:
© FLAIRS 2020.All right reserved.

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

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