Journal of System Simulation
Abstract
Abstract: Cooperative multi-agent path finding (Co-MAPF) has been widely applied in fields such as UAV formation and multi-agent systems, which enhances the overall system efficiency through task collaboration, path planning, and task execution among multiple agents. This paper introduced three main system architectures, namely centralized, distributed, and hybrid, along with their advantages and disadvantages based on the definition of the Co-MAPF problem, categorized, and reviewed mainstream Co-MAPF algorithms, including those based on sampling, search, intelligent optimization, and learning. Furthermore, this paper analyzed the main current challenges faced by Co-MAPF algorithms on the basis of summarizing existing research and outlined the future development directions.
Recommended Citation
Xiong, Jun; Zhang, Wenbo; Xiong, Zhi; Zhou, Feng; and Yang, Bo
(2025)
"Survey of Cooperative Multi-Agent Path Finding,"
Journal of System Simulation: Vol. 37:
Iss.
12, Article 6.
DOI: 10.16182/j.issn1004731x.joss.25-0576
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol37/iss12/6
First Page
3033
Last Page
3049
CLC
TP181
Recommended Citation
Xiong Jun, Zhang Wenbo, Xiong Zhi, et al. Survey of Cooperative Multi-Agent Path Finding[J]. Journal of System Simulation, 2025, 37(12): 3033-3049.
DOI
10.16182/j.issn1004731x.joss.25-0576
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