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Jiacun Wang, Guipeng Xi, Xiwang Guo, Shujin Qin and Henry Han
The scheduling of disassembly lines is of great importance to achieve optimized productivity. In this paper, we address the Hybrid Disassembly Line Balancing Problem that combines linear disassembly lines and U-shaped disassembly lines, considering multi...
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Minseok Kong and Jungmin So
There are several automated stock trading programs using reinforcement learning, one of which is an ensemble strategy. The main idea of the ensemble strategy is to train DRL agents and make an ensemble with three different actor?critic algorithms: Advant...
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Yue Wang, Kexv Li, Xing Zhuang, Xinyu Liu and Hanyu Li
The penetration of unmanned aerial vehicles (UAVs) is an important aspect of UAV games. In recent years, UAV penetration has generally been solved using artificial intelligence methods such as reinforcement learning. However, the high sample demand of th...
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Xiaoyong Zhang, Wei Yue and Wenbin Tang
To enhance the anti-submarine and search capabilities of multiple Unmanned Aerial Vehicle (UAV) groups in complex marine environments, this paper proposes a flexible action-evaluation algorithm known as Knowledge-Driven Soft Actor-Critic (KD-SAC), which ...
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Guangxiu Ning, Lide Su, Yong Zhang, Jian Wang, Caili Gong and Yu Zhou
Due to its flexibility and versatility, the electric distributed drive micro-tillage chassis can be used more often in the future in Intelligence agriculture scenarios. However, due to the complex working conditions of the agricultural operation environm...
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Mohammed Hossny, Julie Iskander, Mohamed Attia, Khaled Saleh and Ahmed Abobakr
Continuous action spaces impose a serious challenge for reinforcement learning agents. While several off-policy reinforcement learning algorithms provide a universal solution to continuous control problems, the real challenge lies in the fact that differ...
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