问题描述
我在学校使用几种AI算法，发现人们使用模糊逻辑一词来解释他们可以通过几种情况解决的任何情况.当我回到书上时，我只是读到关于如何而不是从开"到关"的状态，而是一条对角线，这两种状态都可以存在，但处于不同的级别".
I'm working with a couple of AI algorithms at school and I find people use the words Fuzzy Logic to explain any situation that they can solve with a couple of cases. When I go back to the books I just read about how instead of a state going from On to Off it's a diagonal line and something can be in both states but in different "levels".
我已经阅读了维基百科条目和一些教程，甚至是使用模糊逻辑"的编程内容(边缘检测器和1轮自控机器人)，但从理论到理论，我仍然感到非常困惑.代码...对于您来说，在不太复杂的定义中，什么是模糊逻辑?
I've read the wikipedia entry and a couple of tutorials and even programmed stuff that "uses fuzzy logic" (an edge detector and a 1-wheel self-controlled robot) and still I find it very confusing going from Theory to Code... for you, in the less complicated definition, what is fuzzy logic?
推荐答案
模糊逻辑是一种逻辑，其中状态成员资格实质上是范围为0..1而不是int 0或1的浮点数.例如，您在控制系统中所做的更改自然比在使用天真的二进制逻辑时要微调.
Fuzzy logic is logic where state membership is, essentially, a float with range 0..1 instead of an int 0 or 1. The mileage you get out of it is that things like, for example, the changes you make in a control system are somewhat naturally more fine-tuned than what you'd get with naive binary logic.
一个示例可能是基于活动TCP连接来限制系统活动的逻辑.假设您将计算机上的"TCP连接数过多"定义为1000，将2000定义为太多".在任何给定时间，系统的TCP连接数都从0开始( = 2000)，您可以在应用任何可用的节流机制时将其用作系数.与仅知道如何确定太多"，完全节流或不太多"，根本不节流的幼稚二进制逻辑相比，这对系统行为具有更大的宽容性和响应性.
An example might be logic that throttles back system activity based on active TCP connections. Say you define "a little bit too many" TCP connections on your machine as 1000 and "a lot too many" as 2000. At any given time, your system has a "too many TCP connections" state from 0 (<= 1000) to 1 (>= 2000), which you can use as a coefficient in applying whatever throttling mechanisms you have available. This is much more forgiving and responsive to system behavior than naive binary logic that only knows how to determine "too many", and throttle completely, or "not too many", and not throttle at all.
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