Robotics & Machine Learning Daily News2024,Issue(Apr.23) :81-82.

Report Summarizes Robotics Study Findings from University of Science and Technol ogy China (Effective Offline Robot Learning With Structured Task Graph)

Robotics & Machine Learning Daily News2024,Issue(Apr.23) :81-82.

Report Summarizes Robotics Study Findings from University of Science and Technol ogy China (Effective Offline Robot Learning With Structured Task Graph)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ro botics. According to news reporting out ofHefei, People’s Republic of China, by NewsRx editors, research stated, “Offline reinforcement learning (RL)has shown great potential in many robotic tasks, where doing trial-and-error with the env ironment is risky,costly, or time-consuming. However, it is still hard to succe ed in long-horizon tasks especially when givensuboptimal and multimodal offline datasets.”

Key words

Hefei/People’s Republic of China/Asia/Emerging Technologies/Machine Learning/Robot/Robotics/Robots/University of Science and Technology China

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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