How to generate diverse maps for multi-agent path finding?
A Quality Diversity Approach to Automatically Generate Multi-Agent Path Finding Benchmark Maps
September 12, 2024
https://arxiv.org/pdf/2409.06888This research tackles the challenge of creating diverse and challenging maps for testing multi-agent pathfinding (MAPF) algorithms, specifically using a quality-diversity algorithm and neural cellular automata.
The key takeaway relevant to LLM-based multi-agent systems is the generation of diverse environments (in this case, maps) that expose strengths and weaknesses of different MAPF algorithms. This directly translates to the need for diverse and challenging scenarios when developing and evaluating multi-agent systems driven by LLMs, ensuring robust performance in varied situations.