Abstract
This paper provides a theoretical study on Multi-Objective Heuristic Search. We first classify states in the state space into must-expand, maybe-expand, and never-expand states and then transfer these definitions to nodes in the search tree. We then formalize a framework that generalizes A* to Multi-Objective Search. We study different ways to order nodes under this framework and its relation to traditional tie-breaking policies and provide theoretical findings. Finally, we study and empirically compare different ordering functions.
| Original language | English |
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| 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 | 7021-7028 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781956792041 |
| 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 |
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| ISSN (Print) | 1045-0823 |
Conference
| Conference | 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 |
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| 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.