MPR-RL: Multi-Prior Regularized Reinforcement Learning for Knowledge Transfer

In manufacturing, assembly tasks have been a challenge for learning algorithms due to variant dynamics of different environments. Reinforcement learning (RL) is a promising framework to automatically learn these tasks, yet it is still not easy to apply a learned policy or skill, that is the ability...

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Bibliographic Details
Main Authors:	Stork, J.A (Author), Stoyanov, T. (Author), Yang, Q. (Author)
Format:	Article
Language:	English
Published:	Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:	Aerospace electronics E-learning Job analysis Knowledge management Knowledge transfer Learn+ Learning algorithms Machine learning for robot control Machine-learning Personnel training reinforcement learning Reinforcement learning Reinforcement learnings Robots control Task analysis Trajectories transfer learning Transfer learning
Online Access:	View Fulltext in Publisher

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View Fulltext in Publisher

MPR-RL: Multi-Prior Regularized Reinforcement Learning for Knowledge Transfer

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