人工智能学习指导

双峰和多峰函数最大值的遗传算法求解 采用前向网络-Bimodal and multimodal function maximum use of the genetic algorithm to the network

Boltzmann Machine Optimization 人工智能人工神经网络源码-Boltzmann Machine Optimization of artificial neural network artificial intelligence source

k中心点 编制和调试一个程序，它将用户输入的正规式转换为以状态图和矩阵形式表示的确定有穷自动机。 1．把正规式转换为NFA 2．将NFA确定化为DFA • ＃作为正规式的终止符 • 考虑复合正规式 • 开始状态号为0 -focal point for the preparation of k and debug a program, it will the user to enter the formal conversion to a state diagram and matrix forms express the determination of DFA. 1. The formal type is converted to NFA2. Will determine the NFA into a DFA

基于VC++的小波提升程序，包含小波提升的详细算法。对初学者有很大帮助-Based on VC++ The Wavelet Lifting procedures, including detailed algorithm Wavelet Lifting. Have a great help for beginners

有关神经网络的计算-the neural network computing

fan_nncC语言神经网络程序包-fan_nncC language neural network package

麻省理工大学遗传算法 -Massachusetts Institute of Technology Massachusetts Institute of Technology genetic algorithm genetic algorithm

神 经 网 络 的 资 料-neural network data

机器人足球的程序,机器人足球大赛的有关源代码-robot soccer procedures, the robot soccer competition of the source code

人工股市（Artificial Stock Market，简称ASM）是模拟股市运作的一个程序。在这个电脑中的虚拟市场中，若干被称为交易者的人工智能程序(Agent)通过观察它们所在的数字世界中股价和股息的不断变换而做出预测，并且根据这些预测做出购买股票与否以及购买股票数量的决策。反过来，所有的交易者的决策又决定了股票的价格，这样，整个的股票交易市场就构成了一个自我封闭的计算系统。同时，这些交易者都具有学习的能力，可以根据以前预测的成功或者失败对自己的决策进行调整，并且通过一种被称为遗传算法的方法产生创新能力。-artificial stock market (Artificial Stock Market, or ASM) is a stock market simulation operation of the procedure. In this computer in the virtual market, a number of traders known as artificial intelligence (Agent) by observing them where the digital world and the stock dividend and the constantly changing projections, and based on these projections made whether or not to purchase stocks and the purchase of shares in decision-making. Conversely, all the decision-making transactions in turn determines the share price, so that the entire stock market would constitute a self-enclosed computer system. Moreover, these transactions are capable of learning, can be predicted based on previous success or failure of their decisions for the