The Increasing Cost Tree Search for Optimal Multi-Agent Pathfinding
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 662-666.
Abstract
We address the problem of optimal path finding for multiple agents where agents must not collide and their total travel cost should be minimized. Previous work used traditional single-agent search variants of the A* algorithm. We present a novel formalization for this problem which includes a search tree called the increasing cost tree (ICT) and a corresponding search algorithm that finds optimal solutions. We analyze this new formalization and compare it to the previous state-of-the-art A*-based approach. Experimental results on various domains show the benefits and drawbacks of this approach. A speedup of up to 3 orders of magnitude was obtained in a number of cases.
@inproceedings{ijcai2011p117,
title = {The Increasing Cost Tree Search for Optimal Multi-Agent Pathfinding},
author = {Sharon, Guni and Stern, Roni and Goldenberg, Mark and Felner, Ariel},
booktitle = {Proceedings of the Twenty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-11}},
publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
editor = {Toby Walsh},
pages = {662--666},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-117},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-117},
}
TY - CPAPER TI - The Increasing Cost Tree Search for Optimal Multi-Agent Pathfinding AU - Sharon, Guni AU - Stern, Roni AU - Goldenberg, Mark AU - Felner, Ariel T2 - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11 PB - AAAI Press/International Joint Conferences on Artificial Intelligence PY - 2011 SP - 662 EP - 666 DO - 10.5591/978-1-57735-516-8/IJCAI11-117 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-117 ER -Copied
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