Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Ngo Anh Vien"'
Publikováno v:
IEEE Access, Vol 9, Pp 3638-3648 (2021)
Unmanned aerial vehicle (UAV)-assisted device-to-device (D2D) communications can be deployed flexibly thanks to UAVs' agility. By exploiting the direct D2D interaction supported by UAVs, both the user experience and network performance can be substan
Externí odkaz:
https://doaj.org/article/c6999b71c01b4e28983f78532cda12eb
Publikováno v:
IEEE Access, Vol 7, Pp 164533-164543 (2019)
Device-to-device (D2D) communication is an emerging technology in the evolution of the 5G network enabled vehicle-to-vehicle (V2V) communications. It is a core technique for the next generation of many platforms and applications, e.g. real-time high-
Externí odkaz:
https://doaj.org/article/df3daab963154d1aa51d6faf43d94dc9
Publikováno v:
IEEE Access, Vol 7, Pp 100480-100490 (2019)
Recently, there is the widespread use of mobile devices and sensors, and rapid emergence of new wireless and networking technologies, such as wireless sensor network, device-to-device (D2D) communication, and vehicular ad hoc networks. These networks
Externí odkaz:
https://doaj.org/article/4896b9f86cb04ead9106b474c9ac042f
Publikováno v:
IEEE Access, Vol 6, Pp 49089-49102 (2018)
In recent years, reinforcement learning (RL) has achieved remarkable success due to the growing adoption of deep learning techniques and the rapid growth of computing power. Nevertheless, it is well-known that flat reinforcement learning algorithms a
Externí odkaz:
https://doaj.org/article/3be1a47d41c84d2996029d49b53536eb
Publikováno v:
Applied Intelligence. 50:4050-4062
Meta-learning has recently received much attention in a wide variety of deep reinforcement learning (DRL). In non-meta-learning, we have to train a deep neural network as a controller to learn a specific control task from scratch using a large amount
Publikováno v:
Journal of Computers. 15:1-9
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031198410
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8f1f7ddbdd5c08980508e11a0782d148
https://doi.org/10.1007/978-3-031-19842-7_39
https://doi.org/10.1007/978-3-031-19842-7_39
Meta-learning is widely used in few-shot classification and function regression due to its ability to quickly adapt to unseen tasks. However, it has not yet been well explored on regression tasks with high dimensional inputs such as images. This pape
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b3da59a4f72ad137028e712645eef4d6
Publikováno v:
Adaptive Behavior. 29:253-265
Learning to make decisions in partially observable environments is a notorious problem that requires a complex representation of controllers. In most work, the controllers are designed as a non-linear mapping from a sequence of temporal observations
Publikováno v:
IEEE Access, Vol 7, Pp 100480-100490 (2019)
Nguyen, K K, Duong, T Q, Vien, N A, Le-Khac, N A & Nguyen, M-N 2019, ' Non-Cooperative Energy Efficient Power Allocation Game in D2D Communication: A Multi-Agent Deep Reinforcement Learning Approach ', IEEE Access, vol. 7, pp. 100480-100490 . https://doi.org/10.1109/ACCESS.2019.2930115
Nguyen, K K, Duong, T Q, Vien, N A, Le-Khac, N A & Nguyen, M-N 2019, ' Non-Cooperative Energy Efficient Power Allocation Game in D2D Communication: A Multi-Agent Deep Reinforcement Learning Approach ', IEEE Access, vol. 7, pp. 100480-100490 . https://doi.org/10.1109/ACCESS.2019.2930115
Recently, there is the widespread use of mobile devices and sensors, and rapid emergence of new wireless and networking technologies, such as wireless sensor network, device-to-device (D2D) communication, and vehicular ad hoc networks. These networks