将强化学习算法应用于Tic

遗传算法，是模拟达尔文的遗传选择和自然淘汰的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法.遗传算法是一类可用于复杂系统优化的具有鲁棒性的搜索算法-Genetic algorithm, is a simulation of Darwinian natural selection to genetic selection and biological evolution of the computing model is a natural evolutionary process by simulating the optimal solution search methods. Is a kind of genetic algorithm can be used for optimization of complex systems is robust The search algorithm

用Ｃ语言实现的神经网络，采用遗传算法对网络进行训练，有很快的收敛速度！-C language of neural networks, genetic algorithm was used to train the network, the speed of convergence very soon!

混合生源 加工-Mixed biogenic processing

遗传算法的源代码下载,遗传算法的源代码下载-Genetic algorithm source code download, genetic algorithm source code download

是各种常用算法的集合，又递归、神经网络、遗传、枚举、排序、圆周率求解等等。是学习的好材料。-Is a collection of various commonly used algorithms and recursive, neural networks, genetic, enumeration, sorting, solving, etc. pi. Is a good learning materials.

贝叶斯算法是基于贝叶斯定理 P(H|X) = P(X|H)P(H) / P(X).。对于多属性的数据集，计算 P(X|Ci) 的开销非常大，为减低计算复杂度，我们做条件独立的假设，即给定元组的类标号，假定属性值有条件地相互独立，即在属性间不存在依赖关系。此程序仅为算法的一个实现，根据训练数据训练分类器-Bayesian algorithm is based on the Bayes theorem P (H | X) = P (X | H) P (H)/P (X).. For multi-attribute data sets, computing P (X | Ci) of the overhead is very large, in order to reduce the computational complexity, we do conditional independence assumption that a given tuple class label, it is assumed that property values conditionally independent of each other, that does not exist in the inter-attribute dependencies. This procedure is only an implementation of algorithm, according to training data classifier training

University of Amsterdam的2003年robocup源程序代码，队名trilearn，老牌2D强队-University of Amsterdam

本人编写的QR分解的神经网络算法，该算法用QR分解神经网络的隐含层矩阵，可以作为学术上的比较和分析。适合各种benchmark问题，本人还加了自动产生分类向量和自动适应各种函数的例子-I prepared the QR decomposition of neural network algorithm using QR decomposition neural network hidden layer matrix, can be used as an academic comparison and analysis. Suitable for a variety of benchmark problems, I also added automatically generated classification and automatic vector function to adapt to a variety of examples

人工智能的8数码问题的求解-eight digital artificial intelligence problem solving

该程序比较人性化，有个友好界面，能加载图像，并根据图像训练Hopfield神经网络，你也可以通过添加噪声给图像，以判断它的识别率。-Comparison of the program user-friendly, has a friendly interface that can load images, and in accordance with the training images Hopfield neural network, you can also add noise to images, to determine its recognition rate.