IJCAI 2020poster0 citations
Iterative-Deepening Conflict-Based Search
Eli Boyarski, Ariel Felner, Daniel Harabor, Peter J. Stuckey, Liron Cohen, Jiaoyang Li, Sven Koenig
Abstract
Conflict-Based Search (CBS) is a leading algorithm for optimal Multi-Agent Path Finding (MAPF). CBS variants typically compute MAPF solutions using some form of A* search. However, they often do so under strict time limits so as to avoid exhausting the available memory. In this paper, we present IDCBS, an iterative-deepening variant of CBS which can be executed without exhausting the memory and without strict time limits. IDCBS can be substantially faster than CBS due to incremental methods that it uses when processing CBS nodes.
Planning and Scheduling: Planning and SchedulingAgent-based and Multi-agent Systems: Multi-agent PlanningHeuristic Search and Game Playing: Heuristic Search
BibTeX
@inproceedings{ijcai2020p565,
title = {Iterative-Deepening Conflict-Based Search},
author = {Boyarski, Eli and Felner, Ariel and Harabor, Daniel and Stuckey, Peter J. and Cohen, Liron and Li, Jiaoyang and Koenig, Sven},
booktitle = {Proceedings of the Twenty-Ninth International Joint Conference on
Artificial Intelligence, {IJCAI-20}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Christian Bessiere},
pages = {4084--4090},
year = {2020},
month = {7},
note = {Main track},
doi = {10.24963/ijcai.2020/565},
url = {https://doi.org/10.24963/ijcai.2020/565},
}