Abstract
Research findings on Robotics are discussed in a new report. According to news originating from Guangzhou, People’s Republic of China, by NewsRx correspondents, research stated, “Reinforcement learning (RL) has been successfully applied to a wealth of robot manipulation tasks and continuous control problems. However, it is still limited to industrial applications and suffers from three major challenges: sample inefficiency, real data collection, and the gap between simulator and reality.” Financial supporters for this research include National Natural Science Foundation of China (NSFC), Guangdong Basic and Applied Basic Research Foundation, Industrial Key Technologies R&D Program of Foshan.
NETL
NSTL
Cambridge Univ Press