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Policy abstraction for transfer learning using learning vector quantization in reinforcement learning framework

Policy abstraction for transfer learning using learning vector quantization in reinforcement learning framework

People grow up every day exposed to the infinite state space environment interacting with active biological subjects and machines. There are routines that are always expected and unpredicted events that are not completely known beforehand as well. When people interact with the future routines, they...

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Bibliographic Details
Main Author: Ahmad Afif, Mohd Faudzi
Format: Thesis
Language:English
English
English
Published: 2015
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/13521/
http://umpir.ump.edu.my/id/eprint/13521/
http://umpir.ump.edu.my/id/eprint/13521/1/FKEE%20-%20AHMAD%20AFIF%20MOHD%20FAUDZI.PDF
http://umpir.ump.edu.my/id/eprint/13521/2/FKEE%20-%20AHMAD%20AFIF%20MOHD%20FAUDZI%20-%20CHAP%201.PDF
http://umpir.ump.edu.my/id/eprint/13521/3/FKEE%20-%20AHMAD%20AFIF%20MOHD%20FAUDZI%20-%20CHAP%203.PDF
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http://umpir.ump.edu.my/id/eprint/13521/
http://umpir.ump.edu.my/id/eprint/13521/
http://umpir.ump.edu.my/id/eprint/13521/1/FKEE%20-%20AHMAD%20AFIF%20MOHD%20FAUDZI.PDF
http://umpir.ump.edu.my/id/eprint/13521/2/FKEE%20-%20AHMAD%20AFIF%20MOHD%20FAUDZI%20-%20CHAP%201.PDF
http://umpir.ump.edu.my/id/eprint/13521/3/FKEE%20-%20AHMAD%20AFIF%20MOHD%20FAUDZI%20-%20CHAP%203.PDF

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