Research on local path planning of mobile robot based on Q reinforcement learning and CMAC neural networks.
基于Q强化学习与CMAC神经网络的移动机器人局部路径规划研究。
Using this improved evolutionary neural network, the complex relationship between the design parameters and the stability after reinforcement and the cost of the project is expressed successfully.
利用此进化神经网络较准确地表达了滑坡加固方案中设计参数与加固后滑坡的总体稳定性和工程造价之间的复杂映射关系。
Based on neural network and combined with adaptive capability of reinforcement learning, it can execute velocity tracking control through online learning of neural network.
该控制方法基于神经网络并结合强化学习的自适应能力，通过神经网络的在线学习对车速进行跟踪控制。
By the simulation of a sample path, and the approximation to performance potentials via neural networks based on reinforcement learning (RL), the systems optimization methods are provided.
在样本轨道仿真的基础上，利用神经网络进行强化学习仿真逼近系统的性能势，进而对系统进行优化。
A neural network controller is designed based on reinforcement learning neural network framework to achieve adaptive control of velocity tracking.
然后基于强化学习神经网络结构设计神经网络控制器以取得车速跟踪的自适应控制。
Many factors can be concerned at the same time with artificial neural networks so that the methods of assessment of reinforcement corrosion are both reliable and simple.
用人工神经网络评估混凝土中钢筋锈蚀，可以同时考虑钢筋锈蚀的多种影响因素，使得评估方法既可靠又简单。
For vector control AC drive system, the thesis presented a fuzzy neural network speed controller based on reinforcement learning.
针对矢量控制交流调速系统，该文提出并设计了一种基于再励学习的模糊神经网络速度控制器。
The reinforcement learning is adopted to control and decision for AUV, and Q-learning, BP neural net, artificial potential is integrated to avoidance planning for AUV.
主要采用强化学习的方法对AUV进行控制和决策，综合Q学习算法、BP神经网络和人工势场法对AUV进行避碰规划。
CM_(gs) can interact autonomously with the environment and develop the motor skill by the growing manners of neural system itself through the way of "action –evaluation -reinforcement".
在与对象或环境的交互过程中，通过“行动—评价—改进”的方式，实现自组织的技能学习。
The BP neural network is adopted to realize the reinforcement learning to strengthen the generalization ability.
应用BP神经网络实现强化学习，以增强系统的泛化能力；
And artificial neural network is a valid method to solve the generalization problem for the continuous state and action pairs in the reinforcement learning method.
针对强化学习在连续状态和动作空间的泛化问题，人工神经网络是一种有效的解决方法。
And artificial neural network is a valid method to solve the generalization problem for the continuous state and action pairs in the reinforcement learning method.
针对强化学习在连续状态和动作空间的泛化问题，人工神经网络是一种有效的解决方法。
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