@inproceedings{ba862e118a804be2899d3e77c48c8311,
title = "Hybrid Attack Decision Making with the Introduction of Radar Operating Modes",
abstract = "Radar as the core means of information acquisition, plays a crucial role in air warfare confrontation. However, existing studies on air combat confrontation strategies usually ignore the impact of different radar operating modes on maneuver strategies. To address this problem, this paper investigates the hybrid action decision problem of radar mode and maneuver decision. First, different radar modes are characterized and modeled; then, based on the PPO algorithm, the ineffective actions in the radar strategy are effectively reduced. The simulation experiment results show that the PPO-based reinforcement learning algorithm can realize the efficient synergy between radar and maneuver strategies, and the performance is superior compared with other algorithms.",
keywords = "Decision making, Deep reinforcement learning, Hybrid actions, Radar mode",
author = "Xingyu Wang and Bao Zhang and Ying Zhou and Deyun Zhou",
note = "Publisher Copyright: {\textcopyright} 2025 Technical Committee on Control Theory, Chinese Association of Automation.; 44th Chinese Control Conference, CCC 2025 ; Conference date: 28-07-2025 Through 30-07-2025",
year = "2025",
doi = "10.23919/CCC64809.2025.11179081",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "8869--8873",
editor = "Jian Sun and Hongpeng Yin",
booktitle = "Proceedings of the 44th Chinese Control Conference, CCC 2025",
}