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Committee Date Time Place Paper Title / Authors Abstract Paper #
NC, MBE
(Joint)		 2011-03-07
16:25		 Tokyo Tamagawa University Fusing Learning Strategies to Learn Various Tasks with Single Configuration
Akihiko Yamaguchi, Jun Takamatsu, Tsukasa Ogasawara (NAIST) NC2010-154		 This paper proposes a method to fuse learning strategies (LSs) in reinforcement learning framework. Generally, we need ... [more] NC2010-154
pp.159-164
NC, NLP 2009-07-13
10:30		 Nara NAIST Composition of Feature Space and State Space Dynamics Models for Model-based Reinforcement Learning
Akihiko Yamaguchi, Jun Takamatsu, Tsukasa Ogasawara (NAIST) NLP2009-15 NC2009-8		 Learning a dynamics model and a reward model during reinforcement learning is a useful way, since the agent can also upd... [more] NLP2009-15 NC2009-8
pp.7-12
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
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