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Committee Date Time Place Paper Title / Authors Abstract Paper #
MBE, NC
(Joint)		 2007-12-22
16:10		 Aichi   The Policy Gradient On The Average Reward Manifold
Takamitsu Matsubara (NAIST/ATR), Jun Morimoto (JST/ATR) NC2007-85		 In this paper we propose a novel policy gradient type reinforcement learning method on the average rewardmanifold, in wh... [more] NC2007-85
pp.81-86
MBE, NC
(Joint)		 2007-12-22
16:35		 Aichi   A Modification Algorithm of Function Approximator for the Reinforcement Learning with Reusing Mechanism of Avoidance Actions -- Proposal and its Application to Motion Learning of Multi-Link Robot --
Akihiko Yamaguchi (NAIST), Norikazu Sugimoto, Mitsuo Kawato (ATR-CNS) NC2007-86		 Applying a learning method, such as reinforcement learning, to learning motions of multi-link robots requires large cost... [more] NC2007-86
pp.87-92
NC 2005-10-17
- 2005-10-18		 Kyoto   Effect of climbing fibre input on cerebellar purkinje cell activity
Yuichi Kobayashi (NAIST), Mitsuo Kawato (ATR-CNS), Kenji Kawano (Kyouto-U), Yasushi Kobayashi (Osaka-U) 		 [more] NC2005-39
pp.13-17
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