Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Megumi Miyashita"'
Publikováno v:
Journal of NeuroEngineering and Rehabilitation, Vol 20, Iss 1, Pp 1-9 (2023)
Abstract Background In post-stroke rehabilitation, positive use of affected limbs in daily life is important to improve affected upper-limb function. Several studies have quantitatively evaluated the amount of upper-limb activity, but few have measur
Externí odkaz:
https://doaj.org/article/3f52a78a337642c399b506428a2c0844
Publikováno v:
Results in Control and Optimization, Vol 4, Iss , Pp 100048- (2021)
An important issue in reinforcement learning is to make the agent avoid the dangers and risks during the task such as physical collisions. We propose the reinforcement learning algorithm based on the CoMirror algorithm, named CoMDS, for the problem t
Externí odkaz:
https://doaj.org/article/df31d68901734b48a24a3ced587b9b87
Publikováno v:
Intelligent Autonomous Systems 17 ISBN: 9783031222153
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1b52faa9fe75b8ca444a3e65350300f6
https://doi.org/10.1007/978-3-031-22216-0_5
https://doi.org/10.1007/978-3-031-22216-0_5
Publikováno v:
2022 International Symposium on Micro-NanoMehatronics and Human Science (MHS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a21d78fe533e0c3780dab19a798bdd3a
https://doi.org/10.1109/mhs56725.2022.10092178
https://doi.org/10.1109/mhs56725.2022.10092178
Publikováno v:
2018 Seventh ICT International Student Project Conference (ICT-ISPC).
In the the specific class of black-box optimization algorithms to find the optimal probabilistic distribution of some expected utility in reinforcement learning, higher dimensional decision variables cause the increase of cost and the slowing down of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::63fd5f29a3cb17161ad9b8f4e80f33e1
https://doi.org/10.1109/ict-ispc.2018.8523865
https://doi.org/10.1109/ict-ispc.2018.8523865
Publikováno v:
2017 56th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE).
Considering the connection between black-box optimization problem and reinforcement learning (RL) problem, we can solve a RL problem by black-box optimization algorithm. Especially, extremum seeking (ES) is a notable black-box optimization algorithm,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a83440ed63d068c412403b29a0f36f49
https://doi.org/10.23919/sice.2017.8105470
https://doi.org/10.23919/sice.2017.8105470
Publikováno v:
2017 6th ICT International Student Project Conference (ICT-ISPC).
Recent studies pay attention to the similarity between black-box optimization problem and reinforcement learning (RL) problem. They expect that black-box optimization algorithm can solve RL problems. Among the black-box optimization algorithms, extre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::25c52e8044d17c3d41123de96d68d37a
https://doi.org/10.1109/ict-ispc.2017.8075301
https://doi.org/10.1109/ict-ispc.2017.8075301
In recent years, attention has been focused on the relationship between black-box optimiza- tion problem and reinforcement learning problem. In this research, we propose the Mirror Descent Search (MDS) algorithm which is applicable both for black box
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc68950a5f2646624fed3c0220d888f0
Autor:
Megumi, Miyashita
Publikováno v:
異文化コミュニケーション論集 = Intercultural communication review. 2:75-83
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=jairo_______::ba0108c1b6498b7b9896a024d9955b28
http://id.nii.ac.jp/1062/00005244/
http://id.nii.ac.jp/1062/00005244/
Publikováno v:
Chemical senses. 37(2)
A characteristic astringent taste is elicited by polyphenols. Among the polyphenols, catechins and their polymers are the most abundant polyphenols in wine and tea. A typical green tea polyphenol is epigallocatechin gallate (EGCG). Currently, the mec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::37ac51c0f7a4108d1602104f0e74ac4f
https://pubmed.ncbi.nlm.nih.gov/21890837
https://pubmed.ncbi.nlm.nih.gov/21890837