首页|Data from Nanjing University of Science and Technology Advance Knowledge in Robo tics (State-dependent Maximum Entropy Reinforcement Learning for Robot Long-hori zon Task Learning)
Data from Nanjing University of Science and Technology Advance Knowledge in Robo tics (State-dependent Maximum Entropy Reinforcement Learning for Robot Long-hori zon Task Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Fresh data on Robotics are presented in a new rep ort. According to news reporting originating in Nanjing, People's Republic of Ch ina, by NewsRx journalists, research stated, "Task-oriented robot learning has s hown significant potential with the development of Reinforcement Learning (RL) a lgorithms. However, the learning of long-horizon tasks for robots remains a form idable challenge due to the inherent complexity of tasks, typically comprising m ultiple diverse stages." Funders for this research include National Natural Science Foundation of China ( NSFC), National Natural Science Foundation of China (NSFC), Primary Research & Development Plan of Jiangsu Province, Six talent peaks project in Jiangsu Provin ce.
NanjingPeople's Republic of ChinaAsi aAlgorithmsEmerging TechnologiesMachine LearningReinforcement LearningRobotRoboticsNanjing University of Science and Technology
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