Proceedings

The Increasing Cost Tree Search for Optimal Multi-Agent Pathfinding

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Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 662-666.

https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-117

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.

Guni Sharon, Roni Stern, Mark Goldenberg, and Ariel Felner. 2011. The Increasing Cost Tree Search for Optimal Multi-Agent Pathfinding. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11. IJCAI, 662–666. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-117
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