How can I improve LLM agent pathfinding efficiency?
Transient Multi-Agent Path Finding for Lifelong Navigation in Dense Environments
This paper introduces Transient Multi-Agent Path Finding (TMAPF), a novel approach to improve multi-agent navigation, especially in dense environments like automated warehouses. Unlike traditional methods that require all agents to reach their destinations simultaneously, TMAPF allows agents to reach their targets individually, enhancing flexibility and efficiency. This addresses a key limitation of existing approaches, which struggle in scenarios where agents need to pass each other or share destinations. While the initial experimental results are limited, TMAPF shows promise in complex scenarios by reducing deadlocks, improving throughput (targets reached per time step), and decreasing computational time compared to traditional methods and even some existing LMAPF solutions. The relevance to LLM-based multi-agent systems lies in the potential for LLMs to manage the higher-level coordination and task allocation in such a system, while leveraging TMAPF algorithms for efficient and flexible navigation and path planning of individual agents within the environment.