Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Ingook Jang"'
Publikováno v:
ETRI Journal, Vol 43, Iss 6, Pp 1004-1012 (2021)
AbstractThe collaboration productively interacting between multi‐agents has become an emerging issue in real‐world applications. In reinforcement learning, multi‐agent environments present challenges beyond tractable issues in single‐agent se
Externí odkaz:
https://doaj.org/article/4f51ce3fa2b94ac8a8a49b537deffb65
Publikováno v:
IEEE Access, Vol 8, Pp 146588-146597 (2020)
Deep reinforcement learning (DRL) is a promising approach for developing control policies by learning how to perform tasks. Edge devices are required to control their actions by exploiting DRL to solve tasks autonomously in various applications such
Externí odkaz:
https://doaj.org/article/5613f6ff2a2946caa76f8406e029b013
Publikováno v:
Sensors, Vol 19, Iss 4, p 833 (2019)
The traditional Internet of Things (IoT) paradigm has evolved towards intelligent IoT applications which exploit knowledge produced by IoT devices using artificial intelligence techniques. Knowledge sharing between IoT devices is a challenging issue
Externí odkaz:
https://doaj.org/article/35ad7606074a400e874499a230dd2fb2
Publikováno v:
Sensors, Vol 18, Iss 4, p 1237 (2018)
Energy harvester-integrated wireless devices are attractive for generating semi-permanent power from wasted energy in industrial environments. The energy-harvesting wireless devices may have difficulty in their communication with access points due to
Externí odkaz:
https://doaj.org/article/cabcc7c9cfae4e23b2a24b6db9bb272e
Publikováno v:
ETRI Journal, Vol 43, Iss 6, Pp 1004-1012 (2021)
The collaboration productively interacting between multi‐agents has become an emerging issue in real‐world applications. In reinforcement learning, multi‐agent environments present challenges beyond tractable issues in single‐agent settings.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e5a5b9fa5aa0bddd040b9945ec4e0884
https://doi.org/10.4218/etrij.2021-0010
https://doi.org/10.4218/etrij.2021-0010
Publikováno v:
IEEE Access, Vol 8, Pp 146588-146597 (2020)
Deep reinforcement learning (DRL) is a promising approach for developing control policies by learning how to perform tasks. Edge devices are required to control their actions by exploiting DRL to solve tasks autonomously in various applications such
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c74bf1ab2ed63a2f374145ab82039ed
https://doi.org/10.1109/access.2020.3014922
https://doi.org/10.1109/access.2020.3014922
Publikováno v:
ICTC
Recently, reinforcement learning utilizing deep learning, called deep reinforcement learning, is being developed for discontinuous action space. It is shown that deep reinforcement learning has higher playing skills than those of human in the video g
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ab568b54e14222a3f067c0dbd274d04f
https://doi.org/10.1109/ictc49870.2020.9289596
https://doi.org/10.1109/ictc49870.2020.9289596
Publikováno v:
ICTC
This paper provides an experimental study of reinforcement learning on IoT devices using distilled knowledge, whose a teacher with a well-trained model transfers to a student with a new model to be trained. The experimental results show that the dist
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::02d03bbfe142679fd9552c80604249fa
https://doi.org/10.1109/ictc49870.2020.9289526
https://doi.org/10.1109/ictc49870.2020.9289526
Publikováno v:
ICTC
In area of the reinforcement learning, an environment is important because when a well-known reinforcement learning technique for an environment is applied to another environment, it does not guarantee whether the technique also works well or not. To
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eaed2acce8ad569696d0c6abf17a6cde
https://doi.org/10.1109/ictc46691.2019.8939754
https://doi.org/10.1109/ictc46691.2019.8939754
Publikováno v:
Sensors (Basel, Switzerland)
Sensors, Vol 19, Iss 4, p 833 (2019)
Sensors
Volume 19
Issue 4
Sensors, Vol 19, Iss 4, p 833 (2019)
Sensors
Volume 19
Issue 4
The traditional Internet of Things (IoT) paradigm has evolved towards intelligent IoT applications which exploit knowledge produced by IoT devices using artificial intelligence techniques. Knowledge sharing between IoT devices is a challenging issue
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f26adb145b9a09d9d55760a9cab6801d
https://pubmed.ncbi.nlm.nih.gov/30781639
https://pubmed.ncbi.nlm.nih.gov/30781639