Abstract
In many allocation problems, understanding individual agents' needs, wants, and tradeoffs is crucial for providing fair and efficient solutions. This paper begins with motivating applications and critical definitions. We review existing results, such as advising agents on relaxing restrictions for improved resource allocation, optimizing task allocation in online settings without rejection of a task, and more. We conclude by outlining three potential directions for future research.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 |
| Editors | Kate Larson |
| Publisher | International Joint Conferences on Artificial Intelligence |
| Pages | 8516-8517 |
| Number of pages | 2 |
| ISBN (Electronic) | 9781956792041 |
| DOIs | |
| State | Published - 2024 |
| Event | 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 - Jeju, Korea, Republic of Duration: 3 Aug 2024 → 9 Aug 2024 |
Publication series
| Name | IJCAI International Joint Conference on Artificial Intelligence |
|---|---|
| ISSN (Print) | 1045-0823 |
Conference
| Conference | 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 |
|---|---|
| Country/Territory | Korea, Republic of |
| City | Jeju |
| Period | 3/08/24 → 9/08/24 |
Bibliographical note
Publisher Copyright:© 2024 International Joint Conferences on Artificial Intelligence. All rights reserved.