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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2015
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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 |
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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 |
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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. |
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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 |
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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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1770575439243247616 |