@inproceedings{959c027873ce4e08aa8dc0ce62105289,
title = "Multi-target Strike Planning in Unknown Dynamic Environment",
abstract = "Air-to-air confrontation has attracted wide attention from artificial intelligence scholars. Since the existence of maneuvering targets and various interceptors, the mission autonomous planning of multi-target penetration strikes is difficult in unknown dynamic scenarios. A novel multi-target penetration strike autonomous planning method is proposed in this paper. First, a strike effectiveness function is designed, and dynamic target assignment is achieved through integer programming. Then, a strike planning algorithm based on deep reinforcement learning is designed to realize the autonomous decision-making of penetration in the presence of mission mutation. The simulation result shows that the method can achieve effective multi-target penetration strike in complex combat environments.",
keywords = "Deep reinforcement learning, Mission planning, Target assignment",
author = "Wei Li and Shi Yan and Mian Wang and Yan Liang",
note = "Publisher Copyright: {\textcopyright} 2023, Beijing HIWING Sci. and Tech. Info Inst.; International Conference on Autonomous Unmanned Systems, ICAUS 2022 ; Conference date: 23-09-2022 Through 25-09-2022",
year = "2023",
doi = "10.1007/978-981-99-0479-2\_231",
language = "英语",
isbn = "9789819904785",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "2497--2509",
editor = "Wenxing Fu and Mancang Gu and Yifeng Niu",
booktitle = "Proceedings of 2022 International Conference on Autonomous Unmanned Systems, ICAUS 2022",
}