将强化学习算法应用于Tic

人工智能AI经典入门书，很难找的噢，给喜欢的朋友-classical AI Artificial Intelligence portal, it is very difficult to find the, uh, likes to friends

一个简单灵活的数据挖掘实验平台，算法基本为空，但提供读数据，基本数据预处理功能，欢迎大家使用，共同提高。-a simple and flexible experimental data mining platform, the basic algorithm for air, but for reading data, the basic data preprocessing functions Everyone is welcome to use together.

这个是做自动控制的小车的代码，这里有一些模块的程序，可以参考。-This is the automatic control of the car to do the code, here are some program modules, you can reference.

CCE is a multi-instance learning method solving multi-instance problems through adapting multi-instance representation to single-instance algorithms, which is quite different from existing multi-instance learning algorithms which attempt to adapt single-instance algorithms to multi-instance representation

该程序代码实现BP网络函数逼近，适合初学者学习-The program code to achieve BP network function approximation, suitable for beginners to learn

GENNET是一个通过遗传算法优化权重的16个神经元的全连接神经网络。训练目的是使网络在一定假设的激励下，随时间产生同目标函数同样的响应，即:可以把此网络制作为一个任意波形的信号发生器。 程序分3个示例说明遗传算法进化过程中网络输出的变化趋势。可以看出网络输出（蓝色曲线）随着时间变化逐渐逼近目标函数（红色曲线）。此程序不仅可以学习遗传算法，也可以用于研究全连接网络的直观示例。-GENNET is a genetic algorithm to optimize the weights by the 16 neurons fully connected neural networks. Training purposes is to enable network inspired by certain assumptions, over time, produce the same response with the objective function, namely: the network can be produced as an arbitrary waveform signal generator. Procedure, three examples illustrate the evolution of genetic algorithms in the network output trends. We can see that the network output (blue curve) changes over time, gradually approaching the objective function (red curve). This program can not only learn from the genetic algorithm can also be used to study visual example of a fully connected network.

maltab 的一个遗传算法的例子,比较全,有教你怎么初始化初始种群,设定参数,还有demo提供学习-A genetic algorithm using maltab gentitc toolbox ,abundant in content.Whats s more, you are teached how to initialize the initial population, set parameters. It also provide learning demos.

人工智能中的深度搜索的九宫问题 用VC实现-artificial intelligence, in-depth search of JiuGongTu issue with VC

神经网络C语言源程序-neural network C language source

有指导的马尔可夫随机场（MRF）的图像分割代码，是有指导的方式（即用鼠标框出分类样本区域）。采用OpenCV编写。-Has guided Markov Random Field (MRF) image segmentation code, is guiding the way (that is, a classification of the box with the mouse sample region). Prepared using OpenCV.