%0 Journal Article
%T Application of Reinforcement Learning in Missile Guidance<br>强化学习在导弹制导中的应用
%A ZHOU Rui
%A CHEN Zong-ji
%A <br>周　锐
%A 陈宗基
%J 控制理论与应用
%D 2001
%I 
%X Principle and characteristic of reinforcement learning are outlined. The value function approximation of reinforcement learning with neural networks is studied, and the learning algorithm using modular neural networks to approximate the value function is emphatically analyzed, which decomposes the state space automatically and increases the generalizing ability of the neural networks. The neural networks are trained offline, and is used online as a feedback controller. The A learning algorithm is applied in the missile guidance problem, and the simulation results show the good performance and effectiveness of the application of reinforcement learning in those problems of missile guidance and control.
%K neural networks
%K reinforcement learning
%K differential games
%K missile guidance<br>神经网络
%K 强化学习
%K 微分对策
%K 导弹制导
%K 人工智能
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=3EE6E7135E0B98A5&yid=14E7EF987E4155E6&vid=13553B2D12F347E8&iid=94C357A881DFC066&sid=0B9C8D3D9D6254B2&eid=626A0FE8E3130AB5&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=5