Robotics & Machine Learning Daily News2024,Issue(Oct.25) :49-49.

Reports Summarize Robotics Study Results from Harbin Institute of Technology (Da ta-informed Residual Reinforcement Learning for High-dimensional Robotic Trackin g Control)

Robotics & Machine Learning Daily News2024,Issue(Oct.25) :49-49.

Reports Summarize Robotics Study Results from Harbin Institute of Technology (Da ta-informed Residual Reinforcement Learning for High-dimensional Robotic Trackin g Control)

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Abstract

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 in Harbin, People’s Republic of China, by NewsRx journalists, research stated, “The learning inefficiency of rei nforcement learning (RL) from scratch hinders its practical application toward c ontinuous robotic tracking control, especially for high-dimensional robots. This article proposes a data-informed residual reinforcement learning (DR-RL)-based robotic tracking control scheme applicable to robots with high dimensionality.”

Key words

Harbin/People’s Republic of China/Asia/Emerging Technologies/Machine Learning/Nano-robot/Reinforcement Learning/R obot/Robotics/Robots/Harbin Institute of Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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