Fuzzy logic, according to Zadeh (1997), is the antithesis of rational thinking attributed to the Greek philosopher Aristotle. While rational thinking is focused on precise thinking, which aims to reach the absolute truth, the fuzzy logic assumes the existence of reality as vague, complex and multi-dimensional, and hence the fuzzy logic believes in the existence of non-accuracy as the basic nature of life.

Zadeh, (in Yager, Ovchinnikov, Tong & Nguyen, 1987) clarifies the difference between fuzzy logic and rational thought. Rational thought is a causal model of thinking, essentially linear. For example, if you say that all humans are mortal, it means that Socrates is mortal. This is a simple example of causal-linear reasoning. In Zadeh’s opinion, this is a limited way of thinking about the possibilities of effectively dealing with the complexity of human cognitive processes that are not sequential and causal. He believes that fuzzy logic is more suited for dealing with complex life situations.

Fuzzy logic is defined by Zadeh (1965) as a common sense thinking versus rational thinking that its tendency for accuracy limits the thinking, and therefore the rational thinking can’t be a model for common sense thinking.

Rational thought is a bi-value logic, apparently made so we will see things as “precise” and “exact” (“yes” and “no” or “0” and “1”). Zadeh says that rational classic sets assume that each group has sharp and clear boundaries, such as dead – alive; male – female, etc. But most groups have no sharp boundaries as we would like to have. For example, if we refer to characteristics like height, intelligence, fatigue, illness, after all, these features are absent sharp boundaries. The bi-logic value is not intended to deal with ranking. Ranking, and scaling requires a multi-value logic that can describe real multi-value or partial situations (Yager, Ovchinnikov, Tong & Nguyen, 1987).

Vague quantification options, such as: “many”, “a lot”, “not so much”, etc., are endless. This has implications on the concept of truth as it means that it is okay to say “It is close to the truth” or “It is about right”. In this respect, fuzzy logic provides a flexible way of thinking, based on common sense, to identify and analyze patterns, make decisions, and implement solutions.

It is important to note that fuzzy logic is not a vague, abstract, and confusing model of thinking, it is the opposite. It provides a structured and accurate model to handle situations of inaccuracy, lack of confidence and uncertainty, that lies within the complexity of life and human behavior (Blair, 1994).

Presently, many applications of fuzzy logic are common in technology, economics, psychology, sociology, politics, religion, ethics, law, medicine, and anthropology.