RAILGUN: A Unified Convolutional Policy for Multi-Agent Path Finding Across Different Environments and Tasks
机构 * Thomas Lord Department of Computer Science, University of Southern California(美国南加州大学计算机科学系) ; Independent Researcher(独立研究者) ; Carnegie Mellon University(卡内基梅隆大学) ; University of California, Irvine(加州大学尔湾分校)
专题命中 规划决策 :agent(title,abstract);multi-agent(title,abstract);planning(abstract);分类 cs.AI
Comments 7 pages
Journal ref 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems