Scalable Long-Horizon Planning with Staggered Updates for Lifelong MAPF
Lifelong Multi-Agent Path Finding (LMAPF) requires generating collision-free paths for large agent fleets under strict real-time constraints. Reactive frameworks such as PIBT and Enhanced PIBT (EPIBT) scale effortlessly to thousands of agents through rule-based, step-by-step coordination but suffer from severe temporal myopia, making them ineffective in scenarios where long-horizon reasoning is essential. RHCR plans windowed paths over multi-step horizons but incurs substantial planning overheads that hinder scalability. TP tackles both challenges by planning only subsets of agents at each timestep, yet its applicability is restricted to highly structured maps. To achieve long-horizon pla...
| Authors | Vaibhav Sanjay, Jiaoyang Li |
|---|---|
| Primary category | cs.MA |
| Published | 7 August 2026 |
| Last updated at source | 7 August 2026 |
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