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— Reinforcement learning is a framing of enabling agents to learn from interaction with environments. It has focused generally on Markov decision process (MDP) domains, but a domain may be non-Markovian in the real world. In this paper, we develop a new description of macro-actions for non-Markov decision process (NMDP) domains in reinforcement learning. A(More)
Our purpose in this study was to reduce the noise in order to improve the SNR of Dw images with high b-value by using two correction schemes. This study was performed with use of phantoms made from water and sucrose at different concentrations, which were 10, 30, and 50 weight percent (wt%). In noise reduction for Dw imaging of the phantoms, we compared two(More)
The purpose of this study is to clarify the degree of impregnation resulting from treatment of internal waterlogged wood samples using MRI. On a 1.5T MR scanner, T1 and T2 measurements were performed using inversion recovery and spin-echo sequences, respectively. The samples were cut waterlogged pieces of wood treated with various impregnation techniques(More)
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