首页|Data from North University of China Provide New Insights into Robotics (Reinforc ement Learning Path Planning Method Incorporating Multi-step Hindsight Experienc e Replay for Lightweight Robots)
Data from North University of China Provide New Insights into Robotics (Reinforc ement Learning Path Planning Method Incorporating Multi-step Hindsight Experienc e Replay for Lightweight Robots)
扫码查看
点击上方二维码区域,可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - New research on Robotics is the subject of a repo rt. According to news reporting from Taiyuan,People’s Republic of China, by New sRx journalists, research stated, “Home service robots prioritize costeffectiveness and convenience over the precision required for industrial tasks like auton omous driving,making their task execution more easily. Meanwhile, path planning tasks using Deep Reinforcement Learning(DRL) are commonly sparse reward problem s with limited data utilization, posing challenges in obtainingmeaningful rewar ds during training, consequently resulting in slow or challenging training.”
TaiyuanPeople’s Republic of ChinaAsi aAlgorithmsEmerging TechnologiesMachine LearningNano-robotReinforcemen t LearningRobotRoboticsNorth University of China