|
|
|
|
|
Rick Jaeger, Carolyn Jacobs, Katharina Tondera and Neil Tindale
This study investigated different approaches to optimize flows in misaligned culverts. Structures aligned with the natural stream are always preferred, as misalignments cause a change of direction at the culvert inlet associated with lower performance an...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zheng Li, Xinkai Chen, Jiaqing Fu, Ning Xie and Tingting Zhao
With the development of electronic game technology, the content of electronic games presents a larger number of units, richer unit attributes, more complex game mechanisms, and more diverse team strategies. Multi-agent deep reinforcement learning shines ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jiaming Li, Ning Xie and Tingting Zhao
In recent years, with the rapid advancements in Natural Language Processing (NLP) technologies, large models have become widespread. Traditional reinforcement learning algorithms have also started experimenting with language models to optimize training. ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ahlam A. Abbood, Nazar Oukaili, Abbas A. Allawi and George Wardeh
This study aimed to evaluate the effectiveness of a novel concrete-encased column (CE) using small circular steel tubes filled with cementitious grouting material (GFST) as the primary reinforcement instead of traditional steel bars. The research involve...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jinhui Guo, Xiaoli Zhang, Kun Liang and Guoqiang Zhang
In recent years, the emergence of large-scale language models, such as ChatGPT, has presented significant challenges to research on knowledge graphs and knowledge-based reasoning. As a result, the direction of research on knowledge reasoning has shifted....
ver más
|
|
|
|
|
|
|
|
|
|
|
Sungwon Moon, Seolwon Koo, Yujin Lim and Hyunjin Joo
With recent technological advancements, the commercialization of autonomous vehicles (AVs) is expected to be realized soon. However, it is anticipated that a mixed traffic of AVs and human-driven vehicles (HVs) will persist for a considerable period unti...
ver más
|
|
|
|
|
|
|
|
|
|
|
Dongye Lv, Hanbing Liu, Qiang Miao, Wensheng Wang, Guojin Tan, Chengwei Shi and Hanjun Li
The passivation behavior of steel reinforcements in concrete is significantly influenced by the environment, concrete pore solution, and the passive film formed on the steel surface. The present study used electrochemical methods to successfully characte...
ver más
|
|
|
|
|
|
|
|
|
|
|
Depeng Gao, Shuai Wang, Yuwei Yang, Haifei Zhang, Hao Chen, Xiangxiang Mei, Shuxi Chen and Jianlin Qiu
Servo motors play an important role in automation equipment and have been used in several manufacturing fields. However, the commonly used control methods need their parameters to be set manually, which is rather difficult, and this means that these meth...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ziyi Wang, Xinran Li, Luoyang Sun, Haifeng Zhang, Hualin Liu and Jun Wang
Efficient yet sufficient exploration remains a critical challenge in reinforcement learning (RL), especially for Markov Decision Processes (MDPs) with vast action spaces. Previous approaches have commonly involved projecting the original action space int...
ver más
|
|
|
|
|
|
|
|
|
|
|
Shui Jiang, Yanning Ge, Xu Yang, Wencheng Yang and Hui Cui
Reinforcement learning (RL) is pivotal in empowering Unmanned Aerial Vehicles (UAVs) to navigate and make decisions efficiently and intelligently within complex and dynamic surroundings. Despite its significance, RL is hampered by inherent limitations su...
ver más
|
|
|
|
|
|