Use of the knowledge which is independence on reward in reinforcement learning
Y Miyazaki, K Kurashige - 2009 IEEE International Symposium …, 2009 - ieeexplore.ieee.org
Y Miyazaki, K Kurashige
2009 IEEE International Symposium on Computational Intelligence in …, 2009•ieeexplore.ieee.orgNow, there are some techniques called machine learning, and reinforcement learning is one
of the machine learning which often used for actual machine. In this study, we pay attention
to the knowledge that does not depend on a reward in reinforcement learning, and we will
improve learning efficiency by using it. Furthermore, we aim at letting agent coping with
various tasks under environment where agent is put. In this paper, we propose the
knowledge that does not depend on a reward, and we show utility by applying it to the …
of the machine learning which often used for actual machine. In this study, we pay attention
to the knowledge that does not depend on a reward in reinforcement learning, and we will
improve learning efficiency by using it. Furthermore, we aim at letting agent coping with
various tasks under environment where agent is put. In this paper, we propose the
knowledge that does not depend on a reward, and we show utility by applying it to the …
Now, there are some techniques called machine learning, and reinforcement learning is one of the machine learning which often used for actual machine. In this study, we pay attention to the knowledge that does not depend on a reward in reinforcement learning, and we will improve learning efficiency by using it. Furthermore, we aim at letting agent coping with various tasks under environment where agent is put. In this paper, we propose the knowledge that does not depend on a reward, and we show utility by applying it to the problem that a task turns into under same environment.
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