Zobrazeno 1 - 10
of 2 076
pro vyhledávání: '"LIU Zhihao"'
Recent advancements in solving large-scale traveling salesman problems (TSP) utilize the heatmap-guided Monte Carlo tree search (MCTS) paradigm, where machine learning (ML) models generate heatmaps, indicating the probability distribution of each edg
Externí odkaz:
http://arxiv.org/abs/2406.03503
Autor:
Liu, Zhihao, Yang, Xianliang, Liu, Zichuan, Xia, Yifan, Jiang, Wei, Zhang, Yuanyu, Li, Lijuan, Fan, Guoliang, Song, Lei, Jiang, Bian
Multi-agent reinforcement learning (MARL) is employed to develop autonomous agents that can learn to adopt cooperative or competitive strategies within complex environments. However, the linear increase in the number of agents leads to a combinatoria
Externí odkaz:
http://arxiv.org/abs/2405.16854
Unusual magnetotransport behaviors such as temperature dependent negative magnetoresistance(MR) and bowtie-shaped MR have puzzled us for a long time. Although several mechanisms have been proposed to explain them, the absence of comprehensive quantit
Externí odkaz:
http://arxiv.org/abs/2401.15146
Publikováno v:
Quantum Information Processing, 2020.19(8): p.231
Quantum dense coding plays an important role in quantum cryptography communication, and how to select a set of appropriate unitary operators to encode message is the primary work in the design of quantum communication protocols. Shukla et al. propose
Externí odkaz:
http://arxiv.org/abs/2310.02923
Writing logging messages is a well-established conventional programming practice, and it is of vital importance for a wide variety of software development activities. The logging mechanism in Solidity programming is enabled by the high-level event fe
Externí odkaz:
http://arxiv.org/abs/2308.12788
Multi-agent reinforcement learning (MARL) models multiple agents that interact and learn within a shared environment. This paradigm is applicable to various industrial scenarios such as autonomous driving, quantitative trading, and inventory manageme
Externí odkaz:
http://arxiv.org/abs/2306.07542
Autor:
Guo, Dong1,2 (AUTHOR) qsx20221403@student.fjnu.edu.cn, Liu, Zhihao1,2 (AUTHOR) qsx20221400@student.fjnu.edu.cn, Zhou, Jinglin1,2 (AUTHOR) qsx20211380@student.fjnu.edu.cn, Ke, Chongrong1 (AUTHOR) kechr@fjnu.edu.cn, Li, Daliang1,2 (AUTHOR) kechr@fjnu.edu.cn
Publikováno v:
International Journal of Molecular Sciences. Sep2024, Vol. 25 Issue 18, p9947. 43p.
Autor:
Liu, Zhihao1,2 (AUTHOR), Bian, Xiyun3,4 (AUTHOR), Li, Lan2 (AUTHOR), Liu, Li1,2 (AUTHOR), Feng, Chao5 (AUTHOR), Wang, Ying3,4 (AUTHOR), Ni, Jingyu1 (AUTHOR), Li, Sheng2 (AUTHOR), Lu, Dading3,4 (AUTHOR), Li, Yanxia3,4 (AUTHOR), Ma, Chuanrui1 (AUTHOR), Yu, Tian3,4 (AUTHOR), Xiao, Xiaolin3,4 (AUTHOR), Xue, Na3,4 (AUTHOR), Wang, Yuxiang3,4 (AUTHOR), Zhang, Chunyan3,4 (AUTHOR), Ma, Xiaofang3,4 (AUTHOR), Gao, Xiumei2,6 (AUTHOR), Fan, Xiaohui7,8 (AUTHOR) fanxh@zju.edu.cn, Liu, Xiaozhi3,4 (AUTHOR) lxz7997@126.com
Publikováno v:
Advanced Science. 9/11/2024, Vol. 11 Issue 34, p1-19. 19p.
Publikováno v:
Journal of Intelligent Systems, Vol 33, Iss 1, Pp 1-37 (2024)
With the refinement and scientificization of sports training, the demand for sports performance analysis in the field of sports has gradually become prominent. In response to the problem of low accuracy and poor real-time performance in human pose es
Externí odkaz:
https://doaj.org/article/87e16281cd2444b885e6dfab853842e5
Publikováno v:
BMC Public Health, Vol 24, Iss 1, Pp 1-4 (2024)
Externí odkaz:
https://doaj.org/article/aa8a6bce718343d0b71d61587ab068e9