arXiv: cs.AI preprintsInternational6 November 2026
Goal-Branching LaCAM: Temporary Goals as Search Branches in Dense Multi-Agent Pathfinding
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arXiv:2611.07528v1 Announce Type: new Abstract: LaCAM is a search-based solver for multi-agent pathfinding (MAPF) that runs a depth-first search over joint configurations, using PIBT to generate successors and lazily adding single-agent constraints to explore alternatives. Although LaCAM is complete, it can struggle on dense, corridor-heavy instances because extracting blocking agents from deadlocks requires coordinated moves of several agents, often away from their goals, which PIBT's greedy one-step successors rarely propose and which LaCAM can only reach by enumerating constraints one agent
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