Presentation | 2004/1/19 An experiential learning algorithm for solving maze tasks with episodic memory (Neurocomputing) Yoshito AOTA, Yoko YAMAGUCHI, |
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Abstract(in English) | It is known that Catastrophic interference of learning is one of big problem in the field of learning theory. Although many researchers have tried to conquer this problem, it was imperfect. We consider that this problem is based on natural character of existing learning theories. Because existing methods use some kind of optimization process, sometime it causes interference when the same one situation has not one answer but some answers. In this paper, we propose context dependent action selection system for distinguishing correct situation with episodic memory. The experiential learning algorithm with episodic memory for association of and learning correct contexts is proposed and applied to maze tasks. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Catastrophic interference / episodic memory / learning theory / intelligence / maze task |
Paper # | NC2003-117 |
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Committee | NC |
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Conference Date | 2004/1/19(1days) |
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Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | An experiential learning algorithm for solving maze tasks with episodic memory (Neurocomputing) |
Sub Title (in English) | |
Keyword(1) | Catastrophic interference |
Keyword(2) | episodic memory |
Keyword(3) | learning theory |
Keyword(4) | intelligence |
Keyword(5) | maze task |
1st Author's Name | Yoshito AOTA |
1st Author's Affiliation | Japan Science and Technology Agency (JST), CREST "Creating the Brain"() |
2nd Author's Name | Yoko YAMAGUCHI |
2nd Author's Affiliation | RIKEN, Brain Science Institute |
Date | 2004/1/19 |
Paper # | NC2003-117 |
Volume (vol) | vol.103 |
Number (no) | 601 |
Page | pp.pp.- |
#Pages | 6 |
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