Robotics & Machine Learning Daily News2024,Issue(MAY.15) :57-57.

Reports Outline Robotics Study Results from Gyeonggi Do (Feedback-Based Curricul um Learning for Collision Avoidance)

Robotics & Machine Learning Daily News2024,Issue(MAY.15) :57-57.

Reports Outline Robotics Study Results from Gyeonggi Do (Feedback-Based Curricul um Learning for Collision Avoidance)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on robotics are disc ussed in a new report. According to news reporting originating from Gyeonggi Do, South Korea, by NewsRx correspondents, research stated, “This paper proposes a novel curriculum learning approach for collision avoidance using feedback from t he deep reinforcement learning (DRL) training process. Previous research on DRL- based collision avoidance algorithms has encountered challenges such as long tra ining times and difficulty in convergence due to sparse rewards.”

Key words

Department of Mechanical Design Engineer ing/Gyeonggi Do/South Korea/Asia/Emerging Technologies/Machine Learning/Ro bot/Robotics

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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