Fuzzy Logic can be viewed as a super set of Boolean logic, as a multi-valued logic. It adds degrees between the absolute truth and absolute false to cover partial truth in between. In simple terms, fuzzy logic involves classifying objects and functions into fuzzy sets which could be given linguistic phrases. It is a form of reasoning that is neither exact, nor absolutely inexact. For example, too hot, little slow, phrases which do not give the idea of absolute, but a fuzzy estimate. While 33 degrees might be warm enough for a person from the equator, someone from the arctic might find the heat unbearable, or too hot. It is not possible to classify them into strict sets with defined boundaries which leads to the idea of fuzziness.
It has basically evolved from predicate logic, though many forms called t-norm fuzzy logics do exist in propositional logic too. It generally has an object and a predicate. For example: in the sentence, “Plato is a man”, ‘Plato’ is the object, and “is a man” is the predicate. But an important point about fuzzy logic is that it is deterministic and time-variant. A few salient points explained by Zader Lotfi on fuzzy logic are:
1. Exact reasoning or precise values is the extreme or limiting case of approximate reasoning.
2. Any system which works on logic can be fuzzified and everything would be a matter of degrees.
3. Knowledge is a collection of fuzzy constraints on a group of variables.
The roots of Fuzzy Logic date back to the time when intelligent life forms evolved and they all can be classified as fuzzy systems. While Aristotle, presented the system of two valued logic, it was Plato who laid the foundations of what would be known as fuzzy logic by proposing that there was an intermediate third region in between ‘true’ and ‘not true’ where some part might be true, while some part might not be.
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