Thoughts Decoded

The real world is complex which is full of ambiguities. We say that a person whose height is 6 feet as tall and another who is 5 feet as short. But deciding exactly at what point in between 5 and 6 a short person becomes tall is practically impossible. We can never say that a person who is 5 feet 7 inches is tall and one who is 5 feet 6 is short or even deciding when a new building becomes old one, as the transition from short to tall and new to old is gradual, not abrupt.

The above example is very simple. In our daily life we come across many situations where deciding whether a particular proposition is either true or false is extremely difficult. They can be both true and false at the same time. That is because of the fact that it satisfies both the conditions for being true and false to a certain extent. This is where ambiguity arises. But we are very efficient in deciding these kinds of uncertainties as we get used to perceiving them from very early stages of our life. That is how humans are taught to think and take decisions accordingly. This particular kind of reasoning we employ in understanding things is nothing but “Fuzzy Logic”. We are not aware of our train of thoughts involved in arriving at such conclusions but believe me we do a lot of imprecise reasoning there.

We are very familiar that computers use Boolean or binary logic which deals with 1 and 0 or True and False which means that they take decisions basing on whether or not a particular condition is satisfied. If it satisfies then a certain action is triggered if not something else is done. But as we have observed this is not that useful when it comes to our daily and more practical lives where we are confronted with many half true and half false circumstances. If we want computers to take decisions using a more human like way of thinking we should go for Fuzzy Logic which is why it is so extensively used in Artificial Intelligence. When programmers say reasoning or logic it terrifies most of the non programmers as they are truly frightened of the weird syntax involved in coding. What is very comforting for a lay man about fuzzy logic is that he need not learn anything new in order to use this concept. No. Not even the syntax. All that is required is minimum proficiency in a language (any language). Of course one should know basic definitions involved in fuzzy logic like fuzzy sets, crisp sets, linguistic variables etc. which even a third rate student can understand and use efficiently. Fuzzy logic provides a simple way to arrive at a definite conclusion based upon vague, ambiguous, imprecise input information using a very descriptive language. Simple, plain language rules like If X and Y then Z are used to describe the desired system response in terms of linguistic variables rather than mathematical formulae.

I will do you all a favour by not explaining any of the definitions I stated above as this is not my technical paper on fuzzy logic. I d rather concentrate on how it is useful. We will see an example of a fuzzy air conditioner which is an excellent yet simple usage of fuzzy logic. The If Then rules used in this example are as below

If Cold then Stop.

If Cool then Slow.

If Ok then Medium.

If Warm then Fast.

If Hot then Blast.

As you can see the rules involved are pretty straightforward. These are the basic rules that govern the working of the air conditioner. Observe, we did not use any mathematics here. Just plain English language. The variables (a.k.a. linguistic variables) like cold, cool, ok, warm etc will be converted to mathematical values with the help of Membership Functions. (Membership function is a curve of the degree of truth of a given input value (Forget it if u don’t understand).These mathematical values are then evaluated by the Fuzzy Inference System which is nothing but the fuzzy rules we wrote.

It is that simple. There are many other modules involved in the above example but this is how we primarily use Fuzzy Logic. There are countless applications for fuzzy logic. In fact, some claim that fuzzy logic is the encompassing theory over all types of logic. Automobiles, Cruise control, air conditioners, video cameras, digital image processing, elevators, washing machines, artificial intelligence, bullet trains , medicine are more common applications that one may encounter in everyday life.

Fuzzy systems, including fuzzy logic and fuzzy set theory, provide a rich and meaningful addition to standard logic. The applications which may be generated from or adapted to fuzzy logic are wide-ranging, and provide the opportunity for modeling of conditions which are inherently imprecisely defined. Many systems may be modeled, simulated, and even replicated with the help of fuzzy systems, not the least of which is human reasoning itself.