2. The replication or imitation of biological control setups with the use of technology: The transmission of signals in cybernetics involves those in animal nervous structures and the power over automatic productions of machinery.
Originally, cybernetics drew upon electrical engineering, mathematics, biology, neurophysiology, anthropology, and psychology to study and to describe actions, feedback, and responses in systems of all kinds.
The purpose of cybernetics is to understand the similarities and differences in internal workings of organic and machine processes and, by formulating abstract concepts common to all structures, to understand their behavior.
3. The study of messages and communication in humans, social groups, machines, etc.; especially, in reference to regulation and the circumscription of mechanisms: The analysis of cybernetics in feedback mechanisms serves to govern or to modify the actions of various kinds of programs.Related recent developments of cybernetics (often referred to as "sciences of complexity") that are distinguished as separate disciplines are artificial intelligence, neural networks, systems theory, and chaos theory; however, the boundaries between those and cybernetics proper are not precise.
4. Etymology: coined by U.S. mathematician Norbert Wiener (1894-1964) who hypothesized that there is a similarity between the human nervous system and electronic machines: "Wiener derived the term cybernetics from the Greek kybernetes, 'steersman' (by extension, 'guide, governor') + -ics, 'matters relevant to'; which might have been based on French cybernétique, 'the art of governing'.""Cybernetics is the science of creating machines that are so nearly human that they do things without using any intelligence."
An MIT mathematician named Norbert Wiener (1895-1964) coined the term cybernetics defined the word, which he derived from the Greek (from which also comes the English word "govern"), as the science of communication and control in animals and machines.
Cybernetics referred to an understanding of the animal nervous system, suggesting that a person might consider the brain as a collection of individual neurons that behave much like the binary circuits of a digital computer.
Subsequent research showed that this concept was not correct, but the analogy had a strong effect on biologists, driving them toward a more mathematical and rigorous basis for their own work, and on computer engineers, leading them to think of their creations more as information processing machines than as electronic circuits.