A Review of Deep Reinforcement Learning Methods and Military Application Research
Ning Wang, Zhe Li, Xiaolong Liang, Yueqi Hou, Aiwu Yang
- Year
- 2023
- Citations
- 9
- Access
- Open access
Abstract
In the area of artificial intelligence, deep reinforcement learning has grown in significance. It has accomplished extraordinary feats and offers a fresh approach to previously challenging challenges, such as controlling a robotic arm and discovering game strategies. The two primary categories of deep reinforcement learning methods—deep reinforcement learning based on value function and deep reinforcement learning based on policy gradient—are initially explained in this study. The limitations of current approaches and the difficulties faced by deep reinforcement learning methods in related domains are further sorted out, and then the future application directions of deep reinforcement learning methods in the military sphere are examined. Finally, a growing trend for deep reinforcement learning techniques is anticipated in military applications.
Keywords
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