.png){kind=icon}
.png){kind=icon}
Return
Team collaboration-oriented multi-agent pathfinding and probabilistic verification
.png){kind=icon}
OA
AI
DOI：10.1016/j.inffus.2026.104125.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• Introduces a novel methodology framework that integrates CBS-based multi-agent path finding with probabilistic model checking. • Employs an MDP model to represent multi-agent path execution process, refines model by proposed adjustment solutions, and leverages PRISM for formal verification. • Evaluate the reliability of multi-agent path execution and the robustness of adjustment solutions under stochastic environments.
Keywords:
Goal allocation
Multi-agent pathfinding
Multi-agent path execution
Stochastic environments
Probabilistic model checking
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
15.5
Papers:
4.1K
Citations:
2.7W
View more organizations