Neural network tutorial relatively simple primary comprehensive program design

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

遗传算法在路由优化中的应用:多服务质量的最小路径的算法.-Genetic Algorithm in Routing Optimization: Multi-service quality of the minimum path algorithm.

水木清华BBS精华区－－人工智能 涉及了人工智能的多个方面问题-Shuimu Tsinghua BBS essence District-- AI Artificial Intelligence involves a number of aspects

java　象棋源程序，人工智能，搜索引擎-java chess source, artificial intelligence, search engines

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

在matlab6.5下实现的 -achieved in the matlab6.5

C++神经网络开发包ANNIE，可以用C++语言开发各种神经网络：如BP，RBF，HOPFIELD等，同时随附件带有基于VC和.NET环境的示例源程序 -C neural network development kits 8am, the C language can be used to develop a variety of neural networks : as BP, RBF, Hopfield, along with the annex and with VC.NET environment example source

这是一个自动走迷宫的寻路算法。 可能会有人需要，用作游戏的。 自己新建个Win32空项目，把这个代码复制进去就行了。-This is a Maze of automatic routing algorithm. Some people would argue the need for the game. In their new empty Win32 project, copy this code into there.

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

MCRGSA------组播路由问题遗传模拟退火算法 ％M-----------遗传算法进化代数 ％N-----------种群规模，取偶数 ％Pm----------变异概率调节参数 ％K-----------同一温度下状态跳转次数 ％t0----------初始温度 ％alpha-------降温系数 ％beta--------浓度均衡系数 ％ROUTES------备选路径集 ％Num---------到各节点的备选路径数目 ％Cost--------费用邻接矩阵 ％Source------源节点标号 ％End---------目的节点标号组成的向量 ％MBR---------各代最优路径编码-MCRGSA------ Multicast Routing genetic simulated annealing% M----------- genetic algorithm algebra% N----------- population size, even take Pm----------% probability parameter variation%----------- same temperature K Jump under a number of state----------% t0 initial temperature cooling% alpha------- beta coefficient%-------- balanced concentration coefficient% ROUTES------ Alternative Path Set% Enable--------- nodes to the number of alternative paths%-------- Cost adjacent costs Matrix% Source------ source node labeling% End--------- destination node labeling Group Vector%% of the MBR--------- generations optimal path coding