首页|Study Results from Beijing Institute of Technology Update Understanding of Robot ics (Guided Model-based Policy Search Method for Fast Motor Learning of Robots W ith Learned Dynamics)
Study Results from Beijing Institute of Technology Update Understanding of Robot ics (Guided Model-based Policy Search Method for Fast Motor Learning of Robots W ith Learned Dynamics)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ro botics. According to news reporting originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “Reinforcement learning rec ently has achieved impressive success in allowing robots to learn complex motor skills in simulation environments. However, most of these successes are difficul t to transfer to physical robots since current algorithms require lots of practi cal training and complex sim-to-real transfer skills.”
BeijingPeople’s Republic of ChinaAsi aEmerging TechnologiesMachine LearningNano-robotReinforcement LearningRobotRoboticsBeijing Institute of Technology
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