Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Hongyao Tang"'
Publikováno v:
Molecules, Vol 28, Iss 4, p 1688 (2023)
The application of traditional materials with constant thermal conductivity in time-varying thermal environments poses great challenges due to their inability of adjusting thermal conductivity according to different requirements, for which reason mat
Externí odkaz:
https://doaj.org/article/f75eb6087c1f4112bbb93854ccb50ee3
Publikováno v:
IEEE Transactions on Electron Devices. 69:2030-2037
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031255489
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1b57e99d0bf2d5f22692641316921f9e
https://doi.org/10.1007/978-3-031-25549-6_3
https://doi.org/10.1007/978-3-031-25549-6_3
Publikováno v:
IEEE Transactions on Instrumentation and Measurement. 71:1-9
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030946616
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d0ad235f3dea91f28cfdd49e0dd177a
https://doi.org/10.1007/978-3-030-94662-3_2
https://doi.org/10.1007/978-3-030-94662-3_2
Publikováno v:
Composites Science and Technology. 226:109523
Deep reinforcement learning (DRL) algorithms have been demonstrated to be effective in a wide range of challenging decision making and control tasks. However, these methods typically suffer from severe action oscillations in particular in discrete ac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b2da6430f864c62881615ad517a5713
http://arxiv.org/abs/2103.02287
http://arxiv.org/abs/2103.02287
Autor:
Jianye Hao, Tianpei Yang, Hongyao Tang, Chenjia Bai, Jinyi Liu, Zhaopeng Meng, Peng Liu, Zhen Wang
Deep Reinforcement Learning (DRL) and Deep Multi-agent Reinforcement Learning (MARL) have achieved significant successes across a wide range of domains, including game AI, autonomous vehicles, robotics, and so on. However, DRL and deep MARL agents ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::47db45171643db83668ff72cab473352
Publikováno v:
BIBM
War-game is a type of multi-agent real-time strategy game, with challenges of the large-scale decision-making space and the flexible and changeable battlefield situation. In addition to the military field, it has played a role in fields including epi
Publikováno v:
IJCAI
Reinforcement learning agents usually learn from scratch, which requires a large number of interactions with the environment. This is quite different from the learning process of human. When faced with a new task, human naturally have the common sens