arXiv AI
Goal-Branching LaCAM: Temporary Goals as Search Branches in Dense Multi-Agent Pathfinding
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arXiv AI
Oct 1
Divide and Collapse: MAPF-Collapse via Exact Decomposition into Independent Sub-Instances
arXiv:2609.39559v1 Announce Type: new Abstract: In this work we study the problem of MAPFC, a post-optimization step for Multi-Agent Path Finding (MAPF) plans where we are given a feasible plan produ...
arXiv AI
Jul 2
Planning over MAPF Agent Dependencies via Multi-Dependency PIBT
arXiv:2603. 23405v2 Announce Type: replace-cross Abstract: Modern Multi-Agent Path Finding (MAPF) algorithms must plan for hundreds to thousands of agents in congested environments within a second, requiring highly efficient algorithms.
arXiv AI
Aug 10
Scalable Long-Horizon Planning with Staggered Updates for Lifelong MAPF
arXiv:2608. 06702v1 Announce Type: cross Abstract: Lifelong Multi-Agent Path Finding (LMAPF) requires generating collision-free paths for large agent fleets under strict real-time constraints.
arXiv AI
Sep 30
Do LLM Agents Execute the Plans They Declare? From Planning-Mode Declaration to Pattern-Specific Execution
arXiv:2609.38108v1 Announce Type: new Abstract: Large language models (LLMs) enable agents to solve long-horizon tasks by generating a plan and then executing it in an environment. However, successfu...
arXiv AI
Oct 21
Policy Search in Code Space for Multi-Agent Pathfinding
arXiv:2610.25946v2 Announce Type: replace-cross Abstract: Developing coordination policies for complex multi-agent systems relies on either labor-intensive algorithm design or opaque task-specific re...
arXiv AI
Jun 16
Unassigned Agents in Compilation-based Multi-agent Path Finding
arXiv:2606. 15797v1 Announce Type: new Abstract: Compilation-based techniques represent an important stream of solvers for multi-agent path finding (MAPF) due to their modularity and adaptability for non-standard variants of the problem.