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cs.MA2026
Optimization of Edge Directions and Weights for Mixed Guidance Graphs in Lifelong Multi-Agent Path Finding
Yulun Zhang, Varun Bhatt, Matthew C. Fontaine +2
Multi-Agent Path Finding (MAPF) aims to move agents from their start to goal vertices on a graph. Lifelong MAPF (LMAPF) continuously assigns new goals to agents as they complete cu…
cs.MA2026
QD-MAPPER: A Quality Diversity Framework to Automatically Evaluate Multi-Agent Path Finding Algorithms in Diverse Maps
Cheng Qian, Yulun Zhang, Varun Bhatt +3
We use the Quality Diversity (QD) algorithm with Neural Cellular Automata (NCA) to automatically evaluate Multi-Agent Path Finding (MAPF) algorithms by generating diverse maps. Pre…
cs.MA2024
Guidance Graph Optimization for Lifelong Multi-Agent Path Finding
Yulun Zhang, He Jiang, Varun Bhatt +2
We study how to use guidance to improve the throughput of lifelong Multi-Agent Path Finding (MAPF). Previous studies have demonstrated that, while incorporating guidance, such as h…