Latent Structure Matching for Knowledge Transfer in Reinforcement Learning

Reinforcement learning algorithms usually require a large number of empirical samples and give rise to a slow convergence in practical applications. One solution is to introduce transfer learning: Knowledge from well-learned source tasks can be reused to reduce sample request and accelerate the lear...

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Bibliographic Details
Main Authors: Yi Zhou, Fenglei Yang
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Future Internet
Subjects:
Online Access:https://www.mdpi.com/1999-5903/12/2/36

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