Alan Hayek in (Fuzzy Logic (Standford Encyclopedia of Philosophy) describes : A fuzzy subset A of a (crisp) set X is characterized by assigning to each element x of X the degree of membership of x in A (e.g, X is a group of people, A the fuzzy set of old people in x)

Graph logic model provides exceptional flexibility for expressing of control in various environments of interacting agents.

Attributed logical operators attached to each leaving and coming ends form in fact new basis for control operators for next generation of programming.

FL is a problem-solving control system methodology that lends itself to implementation in systems ranging
from simple, small, embedded micro-controllers to large, networked, multi-channel PC or workstation-based
data acquisition and control systems.

Introduced by Zadeh in 1965: Zadeh, L. (1965), “Fuzzy sets”, Information and Control, 8: 338–353

Fuzzy logic in the narrow sense is symbolic logic with a comparative notion of truth developed fully in the
spirit of classical logic (syntax, semantics, axiomatization, truth-preserving deduction, completeness, etc.; both
propositional and predicate logic). It is a branch of many-valued logic based on the paradigm of inference
under vagueness. This fuzzy logic is a relatively young discipline, both serving as a foundation for the fuzzy
logic in a broad sense and of independent logical interest, since it turns out that strictly logical investigation
of this kind of logical calculi can go rather far.

A definition of fuzzy logic systems set mathematical determination to the emulation of certain perceptual
and lingual attributes related with human cognition, where the science of neural networks provides a new
computing tool with learning and adaptation capabilities.