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About this paper
Hang Ma, Daniel Harabor, Peter J. Stuckey, Jiaoyang Li, Sven Koenig
Researchers from USC and Monash University generalized prioritized planning for Multi-Agent Path Finding (MAPF) by introducing a framework that systematically searches for partial priority orderings. Their algorithms, Conflict-Based Search with Priorities (CBSw/P) and Priority-Based Search (PBS), achieve improved solution quality, higher success rates, and enhanced scalability compared to traditional fixed-priority approaches.
Key insights
- Prioritized planning is fundamentally incomplete and suboptimal for general MAPF problems, even when an optimal solution consistent with some priority ordering exists, which formalizes the need for dynamic priority exploration.
- Systematically searching for and refining partial priority orderings in a conflict-driven manner significantly enhances the robustness and solution quality of prioritized planning while maintaining computational efficiency.
- Sophisticated tie-breaking during low-level path planning, particularly by minimizing collisions with incomparable or lower-priority agents, is critical for improving the overall solution quality in priority-based search algorithms like PBS.
Summary by alphaXiv.
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