Paper Abstract and Keywords |
Presentation |
2005-06-23 13:55
n/a n/a, Takeshi Kamio, Kunihiko Mitsubori, Hisato Fujisaka (n/a) |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
The trade-off between exploration and exploitation has often been discussed in studies on reinforcement learning (RL). This is because exploration and exploitation influence the quality of solutions and the learning efficiency respectively. Previously, we have proposed an adaptive state space segmentation method based on ART neural network for RL. This method is useful for not only the state space segmentation but also the balance between exploration and exploitation. However, if the exploration strength is too large, the learning efficiency degreases rapidly. Since the appropriate strength is generally unknown, this problem must be solved. In this report, we propose a new segmentation method based on ART with two learning phases to improve our conventional method in the tolerance of exploration strength. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Reinforcement Learning / ART Neural Network / State Space / Exploration / Exploitation / / / |
Reference Info. |
IEICE Tech. Rep., vol. 105, no. 125, NLP2005-20, pp. 25-30, June 2005. |
Paper # |
NLP2005-20 |
Date of Issue |
2005-06-16 (NLP) |
ISSN |
Print edition: ISSN 0913-5685 |
Download PDF |
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Conference Information |
Committee |
NLP |
Conference Date |
2005-06-23 - 2005-06-23 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Hiroshima City Univ. |
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(See Japanese page) |
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Paper Information |
Registration To |
NLP |
Conference Code |
2005-06-NLP |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
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(See Japanese page) |
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n/a |
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Keyword(1) |
Reinforcement Learning |
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ART Neural Network |
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State Space |
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Exploration |
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Exploitation |
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Takeshi Kamio |
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n/a (n/a) |
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Kunihiko Mitsubori |
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n/a (n/a) |
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Hisato Fujisaka |
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Speaker |
Author-1 |
Date Time |
2005-06-23 13:55:00 |
Presentation Time |
25 minutes |
Registration for |
NLP |
Paper # |
NLP2005-20 |
Volume (vol) |
vol.105 |
Number (no) |
no.125 |
Page |
pp.25-30 |
#Pages |
6 |
Date of Issue |
2005-06-16 (NLP) |
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