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 language | English |
|---|---|
| Title of host publication | Proceedings of the 33rd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2020 |
| Editors | Eric Bell, Roman Bartak |
| Pages | 213-216 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781577358213 |
| State | Published - 2020 |
| Event | 33rd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2020 - North Miami Beach, United States Duration: May 17 2020 → May 20 2020 |
Publication series
| Name | Proceedings of the 33rd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2020 |
|---|
Conference
| Conference | 33rd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2020 |
|---|---|
| Country/Territory | United States |
| City | North Miami Beach |
| Period | 5/17/20 → 5/20/20 |
Bibliographical note
Publisher Copyright:© FLAIRS 2020.All right reserved.
ASJC Scopus subject areas
- Artificial Intelligence
- Software