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Committee Date Time Place Paper Title / Authors Abstract Paper #
LQE, ED, CPM 2023-12-01
Shizuoka   Fabrication of vertical AlGaN-based UV-B LD
Toma Nishibayashi, Ryosuke Kondo, Eri Matsubara, Ryoya Yamada, Yoshinori Imoto, Koki Hattori, Sho Iwayama, Tetsuya Takeuchi, Satoshi Kamiyama, Motoaki Iwaya (Meijo Univ.), Hideto Miyake (Mie Univ.), Kohei Miyoshi, Koichi Naniwae (Ushio Inc.), Akihiko Yamaguchi (Seishin Trading Co. Ltd.)
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
NC, NLP 2009-07-13
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
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
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