How to plan for agents with fast replanning?
Windowed MAPF with Completeness Guarantees
-
This paper introduces WinC-MAPF, a framework for building multi-agent pathfinding systems that can find solutions within a limited timeframe while guaranteeing completeness (i.e., agents will always reach their goals if a solution exists).
-
Traditional methods struggle with this due to the vast number of potential paths to explore for multiple agents, leading to incomplete solutions when time is limited.
-
WinC-MAPF addresses this by leveraging two key concepts:
- Real-Time Heuristic Search: Inspired by how single-agent systems find paths quickly, it iteratively updates a "cost map" reflecting the desirability of different paths based on prior experience. This helps the system avoid getting stuck in deadlocks.
- Agent Coupling: It focuses on groups of agents directly impacting each other's movements rather than treating all agents equally. This makes the system more efficient, especially in scenarios with many agents.
-
Relevant to LLM-based multi-agent systems, this research offers a way to design systems that can handle complex tasks involving many agents while guaranteeing a solution will be found if one exists, even with time constraints. This is crucial for applications requiring reliable coordination among multiple LLM agents.