首页|Researchers at Chinese Academy of Sciences Have Reported New Data on Robotics (M at: Morphological Adaptive Transformer for Universal Morphology Policy Learning)
Researchers at Chinese Academy of Sciences Have Reported New Data on Robotics (M at: Morphological Adaptive Transformer for Universal Morphology Policy Learning)
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
2024 OCT 08 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Researchers detail new data in Robotics. Accordin g to news originating from Beijing, People's Republic of China, by NewsRx corres pondents, research stated, "Agent-agnostic reinforcement learning aims to learn a universal control policy that can simultaneously control a set of robots with different morphologies. Recent studies have suggested that using the transformer model can address variations in state and action spaces caused by different mor phologies, and morphology information is necessary to improve policy performance ."
BeijingPeople's Republic of ChinaAsiaAlgorithmsEmerging TechnologiesMachine LearningNano-robotRoboticsCh inese Academy of Sciences
NETL
NSTL
