A comparative study between motivated learning and reinforcement learning

This paper analyzes advanced reinforcement learning techniques and compares some of them to motivated learning. Motivated learning is briefly discussed indicating its relation to reinforcement learning. A black box scenario for comparative analysis of learning efficiency in autonomous agents is deve...

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Main Authors: GRAHAM, James T., STARZYK, Janusz A., NI, Zhen, HE, Haibo, TENG, T.-H., TAN, Ah-Hwee
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語言:English
出版: Institutional Knowledge at Singapore Management University 2015
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在線閱讀:https://ink.library.smu.edu.sg/sis_research/5383
https://ink.library.smu.edu.sg/context/sis_research/article/6387/viewcontent/PID3666681.pdf
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機構: Singapore Management University
語言: English
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spelling sg-smu-ink.sis_research-63872020-12-02T04:31:16Z A comparative study between motivated learning and reinforcement learning GRAHAM, James T. STARZYK, Janusz A. NI, Zhen HE, Haibo TENG, T.-H. TAN, Ah-Hwee This paper analyzes advanced reinforcement learning techniques and compares some of them to motivated learning. Motivated learning is briefly discussed indicating its relation to reinforcement learning. A black box scenario for comparative analysis of learning efficiency in autonomous agents is developed and described. This is used to analyze selected algorithms. Reported results demonstrate that in the selected category of problems, motivated learning outperformed all reinforcement learning algorithms we compared with. 2015-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5383 info:doi/10.1109/IJCNN.2015.7280723 https://ink.library.smu.edu.sg/context/sis_research/article/6387/viewcontent/PID3666681.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University motivated learning reinforcement learning goal creation pain signals desired resources Databases and Information Systems Theory and Algorithms
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic motivated learning
reinforcement learning
goal creation
pain signals
desired resources
Databases and Information Systems
Theory and Algorithms
spellingShingle motivated learning
reinforcement learning
goal creation
pain signals
desired resources
Databases and Information Systems
Theory and Algorithms
GRAHAM, James T.
STARZYK, Janusz A.
NI, Zhen
HE, Haibo
TENG, T.-H.
TAN, Ah-Hwee
A comparative study between motivated learning and reinforcement learning
description This paper analyzes advanced reinforcement learning techniques and compares some of them to motivated learning. Motivated learning is briefly discussed indicating its relation to reinforcement learning. A black box scenario for comparative analysis of learning efficiency in autonomous agents is developed and described. This is used to analyze selected algorithms. Reported results demonstrate that in the selected category of problems, motivated learning outperformed all reinforcement learning algorithms we compared with.
format text
author GRAHAM, James T.
STARZYK, Janusz A.
NI, Zhen
HE, Haibo
TENG, T.-H.
TAN, Ah-Hwee
author_facet GRAHAM, James T.
STARZYK, Janusz A.
NI, Zhen
HE, Haibo
TENG, T.-H.
TAN, Ah-Hwee
author_sort GRAHAM, James T.
title A comparative study between motivated learning and reinforcement learning
title_short A comparative study between motivated learning and reinforcement learning
title_full A comparative study between motivated learning and reinforcement learning
title_fullStr A comparative study between motivated learning and reinforcement learning
title_full_unstemmed A comparative study between motivated learning and reinforcement learning
title_sort comparative study between motivated learning and reinforcement learning
publisher Institutional Knowledge at Singapore Management University
publishDate 2015
url https://ink.library.smu.edu.sg/sis_research/5383
https://ink.library.smu.edu.sg/context/sis_research/article/6387/viewcontent/PID3666681.pdf
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