Semantic Tracklets: An Object-Centric Representation for Visual Multi-Agent Reinforcement Learning
Iou-Jen Liu,Zhongzheng Ren,Raymond A. Yeh,Alexander G. Schwing,Iou-Jen Liu,Zhongzheng Ren,Raymond A. Yeh,Alexander G. Schwing
Solving complex real-world tasks, e.g., autonomous fleet control, often involves a coordinated team of multiple agents which learn strategies from visual inputs via reinforcement learning. Many existing multi-agent reinforcement learning (MARL) algorithms however don’t scale to environments where agents operate on visual inputs. To address this issue, algorithmically, recent works have focused on ...
