基于遗传算法的设计生成程序，这是最基本的要求。

【全美经典】小波十讲（Ingrid Daubechies 著）中文版- [ Entire American classics ] wavelet ten lectures (Ingrid Daubechies) Chinese edition

matlab遗传算法源码-Matlab genetic algorithm source code

遗传算法工具箱以及用遗传算法找最优值，主函数是zuiyou.m-Genetic Algorithm Toolbox and using genetic algorithms to find optimal values, the main function is zuiyou.m

一个pso的演示程序,非常经典,对初学者来说是非常不错的学习资料!-A demo program PSO, very classic, for beginners is a very good learning materials!

专家浅谈人工智能，doc文档-expert on artificial intelligence, doc file

AI 人工智能 在C#环境下实现 9宫格 算法-AI

Fisher判别，用于模式识别的Fisher线性判别-Fisher Discriminant for pattern recognition Fisher Linear Discriminant

地球模拟器，最经典的人工生命模型,研究人工智能的必看。一般地说，生命都具有新陈代谢、复制和进化的能力。在自然界中，生物是由有限的食物供给和有限的生存空间约束的。在Tierra中，“生物”由一系列能够自我复制的机器代码或程序组成，它在计算机中的复制分别受到计算机的存储空间和CPU时间约束。能有效地占有内存空间和利用CPU时间的生物体，将具有更高的适应度，传递到下一代的机会就越大。 在Tierra中，计算机的RAM（随机访问存储器）中有一块专门的空间，这个空间中放置了一个“祖先有机体”，该祖先有机体根据它的汇编程序代码中的指令开始复制对它的生存是基本的代码。随着有机体的数目的增加，RAM中的空间减少了，因此有机体为了自己的生存空间开始竞争。-Earth Simulator, the most classic of artificial life model, the study of artificial intelligence Watchable. Generally speaking, life is metabolism, reproduction and the ability of evolution. In nature, biomass is limited by the supply of food and limited living space constraints. In Tierra, "biological" to a series of self-replicating machine code or procedure, in which computers were copied by the computer storage space and CPU time constraints. Effective occupy memory space and CPU time using the organisms, will have a higher degree of adaptability, conveying to the next generation the greater the chances. In Tierra, computer RAM (random access memory) is

遗传算法的工具箱，好使！！！！！！可以解决问题-Genetic algorithm toolbox, so that! ! ! ! ! !

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