Presentation 2004/3/12
Efficiency Improvement of Reinforcement Learning by Sensory Information
Keiji KAMEI, Masumi ISHIKAWA,
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Abstract(in English) Mobile robots severely suffer from slow learning speed of reinforcement learning. To overcome this difficulty, we propose a method for improving its learning efficiency by directly updating a value function based on sensory information. Computer simulation demonstrates the effectiveness of the proposed method; the number of goals reached is about two times larger than that by conventional reinforcement learning in the beginning stage of learning.
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Keyword(in English) reinforcement learning / sensory information / mobile robot / optimal pass
Paper # NC2003-207
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Committee NC
Conference Date 2004/3/12(1days)
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Paper Information
Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Efficiency Improvement of Reinforcement Learning by Sensory Information
Sub Title (in English)
Keyword(1) reinforcement learning
Keyword(2) sensory information
Keyword(3) mobile robot
Keyword(4) optimal pass
1st Author's Name Keiji KAMEI
1st Author's Affiliation Graduate School of Life Science and Systems and Engneering, Kyushu Institute of Technology()
2nd Author's Name Masumi ISHIKAWA
2nd Author's Affiliation Graduate School of Life Science and Systems and Engneering, Kyushu Institute of Technology
Date 2004/3/12
Paper # NC2003-207
Volume (vol) vol.103
Number (no) 734
Page pp.pp.-
#Pages 6
Date of Issue