Presentation 2002/3/11
Acquisition of locomotion by reinforcement learning using neural oscillator network
Yutaka NAKAMURA, Shin ISHII, Masa-aki SATO,
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Abstract(in English) Animal rhythmic movements such as locomotion are considered to be controlled by neural circuits called central pattern generators (CPGs), which generate oscillatory signals. Motivated by such a control mechanism, rhythmic movements controlled by CPG has been studied. In this report, we propose a new reinforcement learning method for CPG controller, which is called the CPG-actor-critic method. We apply this method to the reinforcement learning for the biped robot. The computer simulation shows that our method is able to train the CPG such that the biped robot walks stably.
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Keyword(in English) Reinforcement learning / Actor-critic architecture / Central pattern generator / Neural oscillator network / Bipedal walking
Paper # NC2001-156
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Committee NC
Conference Date 2002/3/11(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Acquisition of locomotion by reinforcement learning using neural oscillator network
Sub Title (in English)
Keyword(1) Reinforcement learning
Keyword(2) Actor-critic architecture
Keyword(3) Central pattern generator
Keyword(4) Neural oscillator network
Keyword(5) Bipedal walking
1st Author's Name Yutaka NAKAMURA
1st Author's Affiliation Nara Institute of Science and Technology()
2nd Author's Name Shin ISHII
2nd Author's Affiliation Nara Institute of Science and Technology:CREST, Japan Science and Technology Corporation
3rd Author's Name Masa-aki SATO
3rd Author's Affiliation ATR Human Information Science Laboratories:CREST, Japan Science and Technology Corporation
Date 2002/3/11
Paper # NC2001-156
Volume (vol) vol.101
Number (no) 735
Page pp.pp.-
#Pages 8
Date of Issue