这是一本较详细介绍遗传算法原理和应用的书籍，很多应用在本书中多有介绍...

旅行推销员问题和野人河，打开一个word文档，包含详细信息

人工智能学习的重要内容，对加强和巩固所学内容将起到非常重要的作用。-AI an important part of learning, to strengthen and consolidate the contents will play a very important role.

这个程序是一个六子棋对弈引擎，采用六子棋标准对弈协议，在对弈平台下可以实现人机对弈或者程序间对弈。具有较好的棋力。-This procedure is a sub-six chess game engine, the use of six sub-standard chess game agreement, in the game platform can be achieved between man-machine chess game or program.棋力good.

这是一个识别两句话之间的相似度的程序，输入是两句中文文字，输出是得分（满分100）-This is a recognition of the similarity between two sentences of the procedure, the input of two Chinese characters, the output is a score (out of 100)

基于Web页面的人工智能控件例证 [VB源码]-Web page based on the example of artificial intelligence control [VB code]

包括883分酒问题，图的遍历等人工智能基本算法-Including 883 hours of liquor problem, artificial intelligence, such as graph traversal algorithm

tsp问题，10个城市的最佳路径。。。。。。matlab-tsp problem, the best 10 cities in the path. . . . . . matlab

用Java编的人工智能的归结反演算法-Java series attributed to the anti-artificial intelligence algorithms

本程序是关于qam的解调程序用c语言编写希望大家能用-this process is on the demodulation process qam c language with hope everyone can be prepared

自组织系统Kohonen网络模型。对于Kohonen神经网络，竞争是这样进行的：对于“赢”的那个神经元c，在其周围Nc的区域内神经元在不同程度上得到兴奋，而在Nc以外的神经元都被抑制。网络的学习过程就是网络的连接权根据训练样本进行自适应、自组织的过程，经过一定次数的训练以后，网络能够把拓扑意义下相似的输入样本映射到相近的输出节点上。网络能够实现从输入到输出的非线性降维映射结构：它是受视网膜皮层的生物功能的启发而提出的。~..~-Kohonen network model. For Kohonen neural network, competition is this : For the "winner" of neurons c, in its switching around the region neurons in varying degrees, to be excited, and the switching outside the neurons were inhibited. Network learning is a process in the network connecting the right under the training samples for adaptive, self-organizing process, after a certain number of training, network topology can sense similar to the mapping of the input samples similar to the output nodes. Network can be achieved from input to output of nonlinear reduced-dimensional mapping structure : it is subject to retinal cortex of the biological function inspired by. ~ ~ ..