Presentation | 2009-03-13 Reinforcement Learning with Internal Rewards Based on Error in a Grid-based Map Yoshifumi TANAKA, Masumi ISHIKAWA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | The present paper proposes to make reinforcement learning efficient by using internal rewards based on curiosity in addition to external rewards at goal in a goal reaching task. Here, curiosity is defined by the decrease in prediction error, which is defined by the difference between grid-based map and the sensory information at each grid. Simulation experiments indicate that the performance of the proposed method is superior to the conventional reinforcement learning in terms of the number of goals reached and the number of actions needed to reach the goal in a transient state. How parameter values affect the performance and learning of the environment is also analyzed. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | reinforcement learning / grid-based map / curiosity / internal reward |
Paper # | NC2008-151 |
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Committee | NC |
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Conference Date | 2009/3/4(1days) |
Place (in Japanese) | (See Japanese page) |
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Paper Information | |
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) | Reinforcement Learning with Internal Rewards Based on Error in a Grid-based Map |
Sub Title (in English) | |
Keyword(1) | reinforcement learning |
Keyword(2) | grid-based map |
Keyword(3) | curiosity |
Keyword(4) | internal reward |
1st Author's Name | Yoshifumi TANAKA |
1st Author's Affiliation | Department of Brain Science and Engineering, Graduate School of Life Science & Engineering, Kyushu Institute of Technology() |
2nd Author's Name | Masumi ISHIKAWA |
2nd Author's Affiliation | Department of Brain Science and Engineering, Graduate School of Life Science & Engineering, Kyushu Institute of Technology |
Date | 2009-03-13 |
Paper # | NC2008-151 |
Volume (vol) | vol.108 |
Number (no) | 480 |
Page | pp.pp.- |
#Pages | 6 |
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