深度强化学习在水下目标识别中的应用研究OACSTPCD

The rapid advancement of deep reinforcement learning signifies a revolutionary progress in the field of artificial in-telligence.By amalgamating the technologies of deep learning and reinforcement learning,it empowers intelligent agents to continu-ously refine and optimize their behaviors in intricate and unfamiliar environments.This article commences with an overview of main-stream algorithms related to reinforcement learning and deep reinforcement learning,dissecting the merits and limitations of existing methods.Furthermore,it meticulously scrutinizes the specific applications of deep reinforcement learning in the military domain,with a particular emphasis on underwater target identification.The analysis extends to a comprehensive evaluation of the practical challenges and issues faced in implementing deep reinforcement learning technologies within military applications.The overarching goal is to stimulate the sustainable development of this technology in the military domain,offering a robust reference for future re-search and practical endeavors.