A Review of Deep Reinforcement Learning Methods and Military Application Research. (10th April 2023)

• Record Type: Journal Article
• Authors: Wang, Ning; Li, Zhe; Liang, Xiaolong; Hou, Yueqi; Yang, Aiwu
• Other Names: Mohammadzadeh Ardashir Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2023(2023)
• Publication Date: 2023-04-10
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2023/7678382
• Languages: English
• ISSNs: 1024-123X

Abstract

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.