Searching with Consistent Prioritization for Multi-Agent Path Finding
Abstract
We study prioritized planning for Multi-Agent Path Finding (MAPF). Existing prioritized MAPF algorithms depend on rule-of-thumb heuristics and random assignment to determine a fixed total priority ordering of all agents a priori. We instead explore the space of all possible partial priority orderings as part of a novel systematic and conflict-driven combinatorial search framework. In a variety of empirical comparisons, we demonstrate state-of-the-art solution qualities and success rates, often with similar runtimes to existing algorithms. We also develop new theoretical results that explore the limitations of prioritized planning, in terms of completeness and optimality, for the first time.
Cite
Text
Ma et al. "Searching with Consistent Prioritization for Multi-Agent Path Finding." AAAI Conference on Artificial Intelligence, 2019. doi:10.1609/AAAI.V33I01.33017643Markdown
[Ma et al. "Searching with Consistent Prioritization for Multi-Agent Path Finding." AAAI Conference on Artificial Intelligence, 2019.](https://mlanthology.org/aaai/2019/ma2019aaai-searching/) doi:10.1609/AAAI.V33I01.33017643BibTeX
@inproceedings{ma2019aaai-searching,
title = {{Searching with Consistent Prioritization for Multi-Agent Path Finding}},
author = {Ma, Hang and Harabor, Daniel and Stuckey, Peter J. and Li, Jiaoyang and Koenig, Sven},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2019},
pages = {7643-7650},
doi = {10.1609/AAAI.V33I01.33017643},
url = {https://mlanthology.org/aaai/2019/ma2019aaai-searching/}
}