蚁群算法的实现，使用一个例子验证蚁群算法的有效性。

k-means算法 自定义数据样本和类中心 已经调试实现 并且有图清晰表示-k-means algorithm for custom data types of samples and testing center has been and realize that has a clear plan

用元胞自动机实现单色10000个空间位置的细菌分裂试验的算法C语言代码-Using Cellular Automata 10,000 monochrome realize spatial location of bacteria to split the test algorithm C language code

利用人工智能原理中BP神经网络算法，建立的彩票预测程序，当然不可能都预测中，但是要学习神经网络的人值得一看-BP neural network algorithm, the establishment of the lottery forecasting process, of course, not all forecasts, but neural networks to study the eye-catcher

围绕粒子群的当前质心对粒子群重新初始化.这样，每个粒子在随后的迭代中将在新的位置带着粒子在上次搜索中获得的“运动惯性”（wvi）向Pi，Pg的方向前进，从而可以在粒子群的运动过程中获得新的位置，增加求得更优解的机会.随着迭代的继续，经过变异的粒子群又将趋向于同一点，当粒子群收敛到一定程度时又进行下一次变异，如此反复，直到迭代结束.-particle swarm around the center of mass of the current PSO reinitialization. Thus, Each particle in the next iteration will be in the new location with particles in the last search was the "inertia" (wvi ) Pi, Pg orientation, and thus can PSO course of the campaign was a new position, increase seek better solutions opportunities. With the continued iteration, after variation of PSO will tend to the same point. When PSO converge to a certain extent when the next variation, so repeatedly, until the end of iteration.

机器人接口程序框架，需要搞机器人的同志不用自己搞框架了-Robot interface program framework, the need to engage in robot comrades do not have to engage in the framework of the

手写汉字识别 应用SVM和神经网络进行识别,可自行训练-Handwritten Chinese Character Recognition Application of SVM and neural networks to identify their own training

人工智能领域最基本的问题-artificial intelligence fundamental problem

BP神经网络的设计前向型神经网络的实例，基于Matlab环境。-BP neural network design to the examples of neural network, based on the Matlab environment.

人工智能的一种典型的启发式搜索算法，是一种最好优先的算法，但要加上一些约束条件。-A typical artificial intelligence heuristic search algorithm, is a priority of the best algorithm, but to add some more restrictive conditions.