Abstract：Faced with the rapidly changing battlefield situation, how to make effective use of intelligent technology to achieve computer-aided decision has become a bottleneck restricting the development of command and control technology. Through the in-depth analysis of the combat decision-making process, it is transformed into an issue of multi-step sequential decision-making. Then the deep learning method is used to extract the characteristic vectors including the commander’s mood, behavior and the decision-making state in the tactics evolution process. The reinforcement learning method is used to search in the action space of decision state and evaluate the decision state until obtaining an optimal action sequence decision, to gain the advantage at the game of machine versus human in the future battlefield.
周来, 靳晓伟, 郑益凯. 基于深度强化学习的作战辅助决策研究[J]. 空天防御, 2018, 1(1): 31-35.
Zhou Lai, Jin Xiaowei, Zheng Yikai. Researchon Operational Decision Support Based on Deep Reinforcement Learning. Air & Space Defense, 2018, 1(1): 31-35.
