AI RESEARCH
Pairwise is Not Enough: Hypergraph Neural Networks for Multi-Agent Pathfinding
arXiv CS.AI
•
ArXi:2602.06733v2 Announce Type: replace-cross Multi-Agent Path Finding (MAPF) is a representative multi-agent coordination problem, where multiple agents are required to navigate to their respective goals without collisions. Solving MAPF optimally is known to be NP-hard, leading to the adoption of learning-based approaches to alleviate the online computational burden. Prevailing approaches, such as Graph Neural Networks (GNNs), are typically constrained to pairwise message passing between agents.