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

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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