Transfer learning through policy abstraction using learning vector quantization

Reinforcement learning (RL) enables an agent to find a solution to a problem by interacting with the environment. However, the learning process always starts from scratch and possibly takes a long time. Here, knowledge transfer between tasks is considered. In this paper, we argue that an abstraction...

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Bibliographic Details
Main Authors: Ahmad Afif, Mohd Faudzi, Takano, Hirotaka, Murata, Jun'ichi
Format: Article
Language:English
Published: UTeM 2018
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/21033/1/Transfer%20learning%20through%20policy%20abstraction.pdf
http://umpir.ump.edu.my/id/eprint/21033/
http://journal.utem.edu.my/index.php/jtec/article/view/3505/2453
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