我在哪里可以得到所有人工智能技术的简单介绍以及真实世界的例子
我知道人工智能领域非常广阔，这方面的书籍也很多。但我只是想知道有什么资源可以对所有人工智能技术进行简单介绍，例如
它希望有 1 或 2 页的所有技术介绍及其示例，说明如何应用它们或它们可以用于什么目的被使用。 感兴趣
- 我对反向传播算法
- 赫布斯定律
- 贝叶斯网络
- 马尔可夫链模型
- 模拟退火
- 禁忌搜索
- 遗传算法或进化算法
现在有很多变体和更多的人工智能技术。每一个都有很多关于它们的书。我无法决定我可以使用哪些算法，除非我知道它们能够做什么。
那么我可以找到 1-2 页的应用示例介绍吗
I know that Artificial Intelligence field is very vast and there are many books on it. But i just want to know the any resource where i can get the simple inroduction to all Artificail Intelligence techniques like
It would like to have 1 or 2 page introduction of all techniques and their examples of how they can be applied or for what purpose they can be used. I am interested in
- Backpropagation Algoritm
- Hebbs Law
- Bayesian networks
- Markov Chain Models
- Simulated Annealing
- Tabu Search
- Genetic Algorithms or Evolutionary Algos
Now there are many variants and more AI techniques. And each one have many books written on them. i am unable to decide which algos i can use unless i know what they are capable of doing.
So can i find 1-2 page inroduction of them with Application examples
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元启发学精要涵盖了其中的几个 - 我不能保证'将涵盖所有内容，但我知道其中有关于模拟退火和遗传算法的好东西。可能至少还有其他一些，但我必须重新下载才能检查。它可以免费下载。
它可能对理论有一点浅显，但它会给你一个简单的描述，一些关于你何时想要使用每个的解释，以及许多有用的伪代码。
Essentials of Metaheuristics covers several of these - I can't promise it'll cover all of them, but I know there's good stuff on simulated annealing and genetic algorithms in there. Probably at least a few of the others, but I'd have to re-download it to check. It's available for free download.
It can be a bit light on the theory, but it'll give you a straightforward description, some explanation of when you'd want to use each, and a lot of useful pseudocode.
这是来自 Drools Planner 手册的本地搜索图像（= 没有禁忌的禁忌搜索） :
我正在为贪婪算法、暴力、分支处理类似的图像以及束缚退火和模拟退火。
Here's an image on local search (= tabu search without tabu) from the Drools Planner manual:
I am working on similar images for Greedy algorithms, brute force, branch and bound and simulated annealing.
作为遗传算法实现的示例，我可以给您这个。
这是我为 GA 开发的一个 API，每个操作员都有一个实现，并解决了一个具体的示例问题（（好）足球队，约有 600 名球员，预算有限）。所有设置都已完成，因此您可以使用 mvn exec:java 运行它并在控制台输出中观察它的演变。但您可以实现自己的问题结构，甚至其他运算符（交叉、变异、选择）方法。
As an example of Genetic Algorithms implementation I can give you this.
It's an API I developed for GA, with one implementation for each operator, and one concrete example problem solved ((good) Soccer Team among ~600 players with budget restriction). Its all setup so you run it with
mvn exec:javaand watch it evolving in the console output. But you can implement your own problem structure, or even other operators (crossing, mutating, selection) methods.