在vc上运行的回答集求解器源代码，能够供在人工智能上学习的学习者使用...

Kohonen的SOFM(自组织特征映射)：这种算法部分收到生物特征影响，在网络输出层内按几何中心或特征进行聚类。-Kohonen the SOFM (self-organizing feature map) : This algorithm received some biological features, the output layer to the network within the geometric center or cluster features.

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

用c语言演绎“生命游戏",本世纪70年代，人们曾疯魔一种被称作“生命游戏”的小游戏，这种游戏相当简单。假设有一个像棋盘一样的方格网，每个方格中放置一个 生命细胞，生命细胞只有两种状态：“生”或“死”。-with language interpretation c Life "game", the 1970s, It had been a crazy demons known as the "Game of Life" of the games, this game is quite simple. Suppose a chessboard like the same grid, each square place a living cell, cell lives only two states : "Health" or "dead."

用A*算法解决八数码问题的小程序，特别好的程序代码-With A* algorithm to solve the problem of a small digital 8 procedures, in particular, a good code

图像检测模板匹配的Visual C++代码-Image Detection template matching Visual C code

将遗传算法与蚁群算法相相结合，产生的一种新算法-genetic algorithm and ant algorithm combination of a new algorithm

基于Viusal C++开发的遗传算法源程序，在VC6.0环境下调试通过。-Based on Viusal C++ Developed genetic algorithm source code in VC6.0 environment debug through.

matlab编写的遗传算法，采用二进制编码，有说明文档。-Matlab prepared by the genetic algorithm, using the binary coding, documentation.

遗传算法简称GA(Genetic Algorithm)，在本质上是一种不依赖具体问题的直接搜索方法。遗传算法在模式识别、神经网络、图像处理、机器学习、工业优化控制、自适应控制、生物科学、社会科学等方面都得到应用。在人工智能研究中，现在人们认为“遗传算法、自适应系统、细胞自动机、混沌理论与人工智能一样，都是对今后十年的计算技术有重大影响的关键技术”。-Referred to as genetic algorithm GA (Genetic Algorithm), in essence is a kind of do not rely on specific issues of direct search method. Genetic algorithm in pattern recognition, neural networks, image processing, machine learning, optimization of industrial control, adaptive control, biological sciences, social sciences and so on have been applied. Research in artificial intelligence, now that the " genetic algorithms, adaptive systems, cellular automata, chaos theory and artificial intelligence, are the next ten years of the computing technology have a major impact on the key technology."

10。《用于最优化的计算智能》，Nirwan Ansali，Edwin Hou着，李军，边肇棋译 清华大学出版社 1999年第一版 本书从讨论组合优化中的基本问题――NP问题入手，系统地讲述了近年来所发展起来的智能最优化的各种技术和方法，其中包括启发式搜索、Hopfield神经网络、模拟退火和随机机、均场退火以及遗传算法等；并在此基础上，通过一些典型的应用问题，如旅行商问题、模式识别中的点模式匹配问题、通信和任务调度等问题进一步阐明以上一些基本方法怎样用来解决这些原来具有NP性质的困难问题。本书是作者在美国新泽西州理工学院多年讲授有关课程的基础上写成的。全书深入浅出，理论联系实际。为帮助学生掌握基本概念，提高学习能动性，各章编写了习题。本书可作为通信、计算机、控制各专业的高年级学生和研究生学习有关课程的教材。它对于广大科研工作者也是一本很有实际价值的参考书。 -10. "Optimal for Computational Intelligence," Nirwan Ansali, with Edwin Hou, Li Jun, Pin Zhaoxing chess translation Tsinghua University Press in 1999 the first book version of combinatorial optimization from the discussion of basic questions-- NP problem start, the system described in recent years to develop the intelligent optimization of the technology and methods, These include heuristic search, Hopfield networks, simulated annealing and random machine, mean field annealing and genetic algorithms; and on this basis and through some typical applications, such as the traveling salesman probl