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Cybernetics

Cybernetics

BIBLIOGRAPHY

The term “cybernetics,” designating a distinct field of activity, appeared on the scientific scene at the close of World War ii, with the publication of Norbert Wiener’s book Cybernetics: Or Control and Communication in the Animal and the Machine. Wiener defined the term “cybernetics” as “the entire field of control and communication theory, whether in the machine or the animal” (Wiener 1948, p. 19); he was unaware that the term had been used, in a more limited sense, a century earlier by André Ampère (1834).

Since 1948, research and publications related to cybernetics have proliferated, unfolding the content of cybernetic concepts and their impact on fields ranging from psychology and neurophysiology to sociology and philosophy of science. This continuing clarification of the meaning and implications of cybernetics has influenced attitudes toward and usage of the term, as well as our understanding of it, thereby blurring Wiener’s initial definition. A brief look at some of the forces that shaped its development will help in understanding what “cybernetics” means today.

In his personal review of the subject, Wiener recounts that while working on the theory of an automatic system for aiming antiaircraft guns he and his colleagues were impressed with the critical role of feedback in the proper functioning of a control system. This led them to conjecture that in order for a person to perform motor activities, his cerebellum must embody types of feedback and associated information processes comparable to those used in an artificial control system. If this were so, then the brain could be viewed as a complex communication, computer, and control system; and the concepts of feedback and control theory could account for internal homeostatic control (for temperature, blood-sugar concentration, heart action, etc.), as well as for control of those motor actions required for purposeful manipulation of external objects. Implicit in these notions was the further thesis that those cognitive activities involved in higher-level problem-solving behavior also could be interpreted mechanistically in terms of the flow and processing of information.

The concepts of cybernetics, emphasizing an information-processing analysis of the mechanisms that generate purposeful behavior, excited the interest of some psychologists, physiologists, and even psychiatrists. Psychologists saw a way of relating behavior to the underlying information processes that control behavior. Neurophysiologists found that the brain and nervous system could be analyzed as a special-purpose computing machine “designed” to generate adaptive, intelligent behavior. And for psychiatrists, Wiener argued that functional mental disorders in the human are primarily diseases of memory caused by errors introduced in the processing of information and are not necessarily indicative of a physiological or anatomical breakdown of the brain mechanism. Thus, Wiener’s writings suggested that problems in the psychology of behavior, the physiology of the nervous system, and the psychopathology of mental disorders could all be described in the neutral language of information processing and control.

Because of the central importance of the concept of information, a second major force behind the development of cybernetics was the publication in 1948 of Shannon’s paper “The Mathematical Theory of Communication.” Here was a theory that explicated quantitatively one measure for the amount of information conveyed by messages. The theory showed how to determine the capacity of a communication channel. One could now compute how much more information one channel could transmit than another. Shannon’s theory clarified the important concept of a code and showed how to determine the efficiency of a given coding system. The theory also demonstrated how to combat the destructive effects of noise by introducing redundancy into coding schemes. Shannon’s mathematical theory of communication not only explicated all of these key concepts but also proved some surprising mathematical relationships between noise, redundancy, channel capacity, and error-free transmission of messages [seeInformation theory].

Clearly, the digital computer was a third force pushing and molding the development of cybernetics. The first electronic digital computer was completed in 1946, and the following years brought swift advances in computer theory, technology, and applications. Switching speeds and memory capacities increased by several orders of magnitude. Input-output devices and information conversion equipment of great diversity were developed. Theoretical foundations emerged in the form of a theory of automata and information machines. More reliable equipment, more flexible programming languages, and a steady decline in costs all contributed to the ever widening use of computers. The application of computing machines spread from scientific calculations to automatic control and businessdata processing—in fact, into almost every facet of government, industrial, and military information processing. One of the most interesting applications is simulation, where the computer is used as a general-purpose research vehicle to generate the logical consequences of arbitrary assumptions about a complex process. Thus, one can get new insights about a complex process by having a computer simulate its behavior, whether the model be for some aspects of the economy or for some neurophysiological structure. In this way psychologists searching for theories of problem-solving behavior (for example, the cognitive behavior associated with proving theorems of logic) have attempted to simulate aspects of such behavior by using a computer. Similarly, neurophysiologists seeking an understanding of the neural organizational principles that give rise to pattern recognition, learning, and similar processes have simulated with computers the behavior of networks of idealized neurons [seeComputation; Simulation].

Wiener’s notions about the brain and the computer, Shannon’s theory of information, and the new computing technology created optimism about new ways to attack the formidable problems of thinking and knowing. This atmosphere of excitement and ferment, accentuated by hopes of interdisciplinary unification, generated much competent work. Unfortunately, it also produced serious intellectual and semantic misunderstandings about computers, brains, and people; and confusions between information and meaning, between amount of information and entropy. These difficulties caused some nonsensical claims to be offered under the banner of cybernetics. The more responsible workers criticized this pseudoscientific fringe, thereby contributing to a reversal in attitudes. The new tendency was to regard cybernetics with suspicion and disdain.

Thus, there developed—and still exist—conflicting attitudes toward cybernetics and what its subject matter really is. Vagueness about the meaning of “cybernetics” has been compounded by the fact that since around 1955 the subject of cybernetics has enjoyed a wide acceptance and publicity in the Soviet Union, where it is now interpreted most broadly and used to describe all studies and techniques that relate even in the most remote way to computers, information processing, communications, or control systems.

Today, almost two decades after Wiener’s book, “cybernetics” still means different things to different people. For some, cybernetics is not a “new science” but merely a collection of techniques, studies, and devices clustering around information processing. For those who accept this interpretation, “cybernetics” is but a fancy name for the application of certain techniques to related fields— for example, the application of information theory to analysis of coding and redundancy in the visual sensory system.

Others equate cybernetics with automation and its accelerating thrust into all facets of human activity. They recognize that cybernetics not only changes favorably the face of our society but also initiates sociological problems of great magnitude —such as technological unemployment and social conflict resulting from the increasing replacement of men by machines.

Finally, many interpret cybernetics as a new, all-inclusive, and powerful way of analyzing complex systems, from machines to society itself, in terms of the flow and processing of information. Some of these see a deeper significance to the underlying logical structure of cybernetics. The concepts of cybernetics do, in fact, offer hope for a new unity in our understanding of those processes that underlie the activities of knowing.

For some, the real intellectual wealth of cybernetics lies not in its analogies between the computer and the brain—though these analogies are fruitful—but rather in the realization that both systems, natural and artificial, can be analyzed in terms of the same cybernetic language, the language of information and control (see MacKay 1957 for a more detailed discussion). The concepts of this language are potentially rewarding because they span the traditional gap between the psychology of behavior and the physiology of those mechanisms that generate behavior, including cognitive behavior. Thus, cybernetics offers an effective new language for analyzing those information mechanisms and processes associated with behavioral aspects of thinking and knowing. The language of cybernetics may prove rich and versatile enough to permit a theory of knowing—a science of knowledge—to be expressed in terms of cybernetic concepts.

Those concepts suggest even more than how to grasp and formulate the relationship between the information-flow organization of the brain and intelligent behavior. There is no reason to believe that the human brain and nervous system is optimally organized. One might find principles, framed in cybernetic language, that show how to design an artifact able to learn more quickly, remember and associate better, act faster and more reliably, or solve problems more ingeniously than humans. One might find design principles radically different from those embodied in the human, and build (or grow) highly intelligent artifacts. All of this presupposes, of course, a theory of thinking and knowing (as exists for engineering communications) that can be used to judge which cognitive system is optimal relative to some aspect of information processing. Be clear about what this means. Cybernetics today offers no laws describing what kinds of information-flow structures are necessary to produce various dimensions of intelligent (mindlike) behavior. There exist only the faintest outlines of such organizational principles. Nothing, however, contradicts the thesis that such design principles exist, can be described, and can be implemented. Cybernetics offers both a language and a set of concepts to use in molding these principles into a theory relating information processing to the activities of learning, thinking, knowing, and understanding (see Maron 1965).

M. E. Maron

[Directly related is the biography ofWiener. Other relevant material may be found inComputation; Information theory; Simulation.]

BIBLIOGRAPHY

AmpÉre, AndrÉ; Marie (1834) 1856 Essai sur la philosophie des sciences: Ou exposition analytique d’une classification naturelle de toutes les connaissances humaines. 2d ed. Paris: Mallet-Bachelier.

Ashby, William R. (1956) 1961 An Introduction to Cybernetics. London: Chapman.

George, Frank H. 1961 The Brain as a Computer. New York: Pergamon.

Kybernetik. → Published since 1960, mostly in German; the emphasis is on bio-cybernetics.

MacKay, D. M. (1957) 1964 Information Theory in the Study of Man. Pages 214–235 in John Cohen (editor), Readings in Psychology. London: Allen & Unwin.

Maron, M. E. 1965 On Cybernetics, Information Processing, and Thinking. Pages 118–138 in Norbert Wiener and J. P. Schadé (editors), Cybernetics of the Nervous System. Progress in Brain Research, Vol. 17. Amsterdam: Elsevier.

Shannon, Claude E. 1948 The Mathematical Theory of Communication. Bell System Technical Journal 27: 379–423, 623–656.

Shannon, Claude E.; and Weaver, Warren (1949) 1959 Mathematical Theory of Communication. Urbana: Univ. of Illinois.

Wiener, Norbert (1948) 1962 Cybernetics: Or Control and Communication in the Animal and the Machine. 2d ed. Cambridge, Mass.: M.I.T. Press.

Wiener, Norbert (1950) 1954 The Human Use of Human Beings: Cybernetics and Society. 2d ed. Boston: Houghton Mifflin.

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Cybernetics

Cybernetics

The term cybernetics is much misused in the popular media. Often used to convey notions of high-technology, robotics , and even computer networks like the Internet, in reality, cybernetics refers to the study of communications and control in animal and machine.

Great mathematicians of the past such as Wilhelm Leibniz (16461716) and Blaise Pascal (16231662) had been interested in the nature of computing machinery long before these machines had ever been realized. They concerned themselves with philosophizing over what special peculiarities might be present in machines that had the ability to compute. In the mid-1930s Alan Turing (19121954) developed the idea of an abstract machine (later to become known as the "Turing Machine" ). Turing machines introduced the possibility of solving problems by mechanical processes that involved a machine stepping through a sequence of states under the guidance of a controlling element of some sort. This laid the fundamental groundwork that was then developed by Norbert Wiener (18941964) into what has become cybernetics.

In 1948 Wiener concluded that a new branch of science needed to be developed. This field would draw from the realms of communication, automatic control, and statistical mechanics. He chose the word cybernetics, deriving it from the Greek word for "steersman" which underlines one of the essential ingredients of this fieldthat of governance or control. He defined cybernetics to be "control and communication in the animal and the machine." What really makes cybernetics stand apart from other fields in science and engineering is that it focuses on what machines do rather than the details of how they actually do it.

Classically, the study of a particular piece of conventional mechanical machineryfor example, a typewriterwould not be considered complete until all of the intricacies of the physics of movement of the constituent parts had been accounted for. This constitutes a Newtonian view of systemsone that commences with a perspective of Newtonian mechanics and builds from there. Cybernetics, on the other hand, accentuates the behavior and function of the machine as a whole. The result of this stance is that cybernetics is not restricted to dealing with mechanical or perhaps electrical machines only; instead it applies to anything that might possibly be viewed in some way as a machineincluding organisms. That is, cybernetics looks at all the elements that are common denominators in that class of entities that might describe as machines. Wiener concluded that for a system to be classed as cybernetic, communication between parts of a system was a necessary characteristic, as was feedback from one part to another. The presence of feedback means that a cybernetic system is able to measure or perceive a quantity of some sort, then compare this to a required or desired value, and then instigate some strategy or behavior that affects change in that quantity. This is as much true of a heater and thermostat used to regulate temperature in a house, as it is of a bird that seeks refuge in a bird bath on a hot day.

Historically, the human body, in particular the human brain, has been viewed by many as a type of machine. This perception was generated by people who were hopeful of finding a way of modeling human behavior in the same way that they could model human-made machinesan approach with which they were comfortable. Much effort was directed toward understanding the operation of the human brain in this light.

Throughout the nineteenth and early twentieth centuries, significant advances were made in understanding the physiology of the human brain. Research into the structure of the cerebral cortex, the discovery of the brain as the center of perception, and the identification of neurones and synapses were all contributors to the conclusion that the brain is the regulator, controller, and seat of behavior of the human species. Because these ideas are fundamental to cybernetics, the human brain and the notion of intelligence are also considered as subjects that are within the realm of the cybernetic field. As a consequence, a great deal of research has been carried out in the areas of biological control theory, neural modeling , artificial intelligence (AI) , cognitive perception, and chaos theory from a perspective that resulted from the development of cybernetics.

With respect to computer systems, cybernetics has been prominent in two areas. The first is artificial intelligence, where computer algorithms have been developed that attempt to exhibit some traits of intelligent behaviorinitially by playing games and later by processing speech and carrying out complex image and pattern manipulation operations. The second is in robotics, which frequently encompasses artificial intelligence and other cybernetic areas such as communication and automatic control using feedback. Early robotic systems were nothing more than complex servo-mechanisms that carried out manual tasks in place of a human laborer; however, the modern cybernetic approach is to attempt to construct robots that can communicate and be guided toward acting together as a team to achieve a collective goal. This has generated interest in a new type of adaptive machine that has the capacity to re-organize its strategies and behavior if its environment or mission changes.

Finally, beyond a computing context, cybernetics offers some advantages in our understanding of nature. First, it permits a unified approach to studying and understanding machine-like systems. This results from the distinct way in which the cybernetic viewpoint of systems is formulated; it is not restricted to particular machine or system types. For example, we can draw a correspondence between an electro-mechanical system like a collection of servo-motors and linkages that give a robot locomotion, and a biological system like the nervous and musculo-skeletal systems of a caterpillar. One is not required to undertake greatly differing analyses to gain an appreciation of both. Secondly, it offers a manageable way of dealing with the most predominant type of systemone that is highly complex, non-linear, and changes over time.

see also Artificial Intelligence; Robotics; Space Travel and Exploration.

Stephen Murray

Bibliography

Arbib, Michael A. Brains, Machines, and Mathematics, 2nd ed. New York: Springer-Verlag, 1987.

Ashby, W. Ross. An Introduction to Cybernetics. London: Chapman and Hall Ltd., 1971.

Caianiello, E. R., and G. Musso, eds. Cybernetic Systems: Recognition, Learning, Self-Organisation. Letchworth: Research Studies Press Ltd., 1984.

Glorioso, Robert M. Engineering Cybernetics. Englewood Cliffs: Prentice-Hall Inc., 1975.

Wiener, Norbert. Cybernetics or Control and Communication in the Animal and the Machine, 2nd ed. Cambridge: MIT Press, 1961.

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cybernetics

cybernetics is the science of control. Its name, appropriately suggested by the mathematician Norbert Wiener (1894–1964), is derived from the Greek for ‘steersman’, pointing to the essence of cybernetics as the study and design of devices for maintaining stability, or for homing in on a goal or target. Its central concept is feedback. Since the ‘devices’ may be living or man-made, cybernetics bridges biology and engineering.

Stability of the human body is achieved by its static geometry and, very differently, by its dynamic control. A statue of a human being has to have a large base or it topples over. It falls when the centre of mass is vertically outside the base of the feet. Living people make continuous corrections to maintain themselves standing. Small deviations of posture are signalled by sensory signals (proprioception) from nerve fibres in the muscles and around the joint capsules of the ankles and legs, and by the otoliths (the organs of balance in the inner ear). Corrections of posture are the result of dynamic feedback from these senses, to maintain dynamic stability. When walking towards a target, such as the door of a room, deviations from the path are noted, mainly visually, and corrected from time to time during the movement, until the goal is reached. The key to this process is continuous correction of the output system by signals representing detected errors of the output, known as ‘negative feedback’. The same principle, often called servo-control, is used in engineering, in order to maintain the stability of machinery and to seek and find goals, with many applications such as guided missiles and autopilots.

The principles of feedback apply to the body's regulation of temperature, blood pressure, and so on. Though the principles are essentially the same as in engineering, for living organisms dynamic stability by feedback is often called ‘homeostasis’, following W. B. Cannon's pioneering book The wisdom of the body (1932). In the history of engineering, there are hints of the principle back to ancient Greek devices, such as self-regulating oil lamps. From the Middle Ages the tail vane of windmills, continuously steering the sails into the veering wind, are well-known early examples of guidance by feedback. A more sophisticated system reduced the weight of the upper grinding stone when the wind fell, to keep the mill operating optimally in changing conditions. Servo-systems using feedback can make machines remarkably life-like. The first feedback device to be mathematically described was the rotary governor, used by James Watt to keep the rate of steam engines constant with varying loads.

Servo-systems suffer characteristic oscillations when the output overshoots the target, as occurs when the feedback is too slow or too weak to correct the output. Changing the ‘loop gain’ (i.e. the magnitude of correction resulting from a particular feedback signal) increases tremor for machines and organisms. It is tempting to believe that ‘intention tremor’ of patients who have suffered damage to the cerebellum is caused by a change in the characteristics of servo control.

Dynamic control requires the transmission of information. Concepts of information are included in cybernetics, especially following Claud Shannon's important mathematical analysis in 1949. It does not, however, cover digital computing. Cybernetic systems are usually analogue, and computing is described with very different concepts. Early Artificial Intelligence (AI) was analogue-based (reaching mental goals by correcting abstract errors) and there has recently been a return to analogue computing systems, with self-organizing ‘neural nets’.

A principal pioneer of cybernetic concepts of brain function was the Cambridge psychologist Kenneth Craik, who described thinking in terms of physical models analogous to physiological processes. Craik pointed to engineering examples, such as Kelvin's tide predictor, which predicted tides with a system of pulleys and levers. The essential cybernetic philosophy of neurophysiology is that the brain functions by such principles as feedback and information, represented by electro-chemical, physical activity in the nervous system. It is assumed that this creates mind: so, in principle, and no doubt in practice, machines can be fully mindfu.

Richard L. Gregory

Bibliography

Cannon, W. B. (1932). The wisdom of the body. New York.
Craik, K. J. W. (1943). The nature of explanation. Cambridge.
Mayr, O. (1970). The origins of feedback control. Cambridge, M.A.
Shannon, C. E. and and Weaver, W. (1949). The mathematical theory of information. Urbana.
Weiner, N. (1948). Cybernetics. New York.


See also balance; homeostasis; proprioception; vestibular system.

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Cybernetics

Cybernetics

Cybernetics is the study of communication and control processes in living organisms and machines. Cybernetics analyzes the ability of humans, animals, and some machines to respond to or make adjustments based upon input from the environment. This process of response or adjustment is called feedback or automatic control. Feedback helps people and machines control their actions by telling them whether they are proceeding in the right direction.

For example, a household thermostat uses feedback when it turns a furnace on or off based on its measurements of temperature. A human being, on the other hand, is such a complex system that the simplest action involves complicated feedback loops. A hand picking up a glass of milk is guided continually by the brain that receives feedback from the eyes and hand. The brain decides in an instant where to grasp the glass and where to raise it in order to avoid collisions and prevent spillage.

The earliest known feedback control mechanism, the centrifugal governor, was developed by the Scottish inventor James Watt in 1788. Watt's steam engine governor kept the engine running at a constant rate.

Systems for guiding missiles

The principles for feedback control were first clearly defined by American mathematician Norbert Wiener (18941964). With his colleague Julian Bigelow, Wiener worked for the U.S. government during World War II (193945), developing radar and missile guidance systems using automatic information processing and machine controls.

After the war, Wiener continued to work in machine and human feedback research. In 1950, he published The Human Use of Human Beings: Cybernetics and Society. In this work, Wiener cautioned that an increased reliance on machines might start a decline in human intellectual capabilities. Wiener also coined the word "cybernetics," which comes from the Greek word kybernetes, meaning "steersman."

Words to Know

Artificial intelligence (AI): The science that attempts to imitate human intelligence with computers.

Feedback: Information that tells a system what the results of its actions are.

Robotics: The science that deals with the design and construction of robots.

Cybernetics and industry

With the advent of the digital computer, cybernetic principles such as those described by Wiener were applied to increasingly complex tasks. The result was machines with the practical ability to carry out meaningful work. In 1946, Delmar S. Harder devised one of the earliest such systems to automate the manufacture of car engines at the Ford Motor Company. The system involved an element of thinking: the machines regulated themselves, without human supervision, to produce the desired results. Harder's assembly-line automation produced one car engine every 14 minutes, compared with the 21 hours if had previously taken human workers.

By the 1960s and 1970s, the field of cybernetics, robotics, and artificial intelligence began to skyrocket. A large number of industrial and manufacturing plants devised and installed cybernetic systems such as robots in the workplace. In 1980, there were roughly 5,000 industrial robots in the United States. By the early twenty-first century, researchers estimated there were as many as 500,000.

Considerable research is now focused on creating computers that imitate the workings of the human mind. The eventual aim, and the continuing area of research in this field, is the production of a neural computer, in which the architecture of the human brain is reproduced. The system would be brought about by transistors and resistors acting such as neurons, axons, and dendrites do in the brain. The advantage of neural computers is they will be able to grow and adapt. They will be able to

learn from past experience and recognize patterns. This will enable them to operate intuitively, at a faster rate, and in a predictable manner.

[See also Artificial intelligence; Computer, digital; Robotics ]

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Cybernetics

Cybernetics


The term cybernetics is derived from the Greek word kybernetes (steersman). The term was introduced in 1948 by the mathematician Norbert Wiener (18941964) to describe how systems of information and control function in animals and machines (steersmanship). Cybernetics is inherently interdisciplinary; it is related to systems theory, chaos theory, and complexity theory, as well as artificial intelligence, neural networks, and adaptive systems. Cybernetics was formulated by thinkers such as Wiener, Ludwig von Bertalanffy (19011972), W. Ross Ashby (1903-1972), and Heinz von Foerster (1911). It developed as a consequence of multidisciplinary conversations among thinkers from a variety of disciplines, including economics, psychiatry, life sciences, sociology, anthropology, engineering, chemistry, philosophy, and mathematics. Cybernetics contributed greatly to the development of information theory, artificial intelligence, artificial life, and it foresaw much of the work in robotics and autonomous agents (hence the term cyborg for robot).

After control engineering and computer science became independent disciplines, some cyberneticists felt that more attention needed to be paid to a system's autonomy, self-organization, and cognition, and the role of the observer in modeling the system. This approach became known as second-order cybernetics in the early 1970s. Second-order cybernetics emphasizes the system as an agent in its own right and investigates how observers construct models of the systems with which they interact. At times, second-order cybernetics has resulted in the formulation of philosophical approaches that, according to some critics, are in danger of losing touch with concrete phenomena.

Cybernetics moves beyond Newtonian linear physics to describe and control complex systems of mutual causalities and nonlinear time sequences involving feedback loops. It seeks to develop general theories of communication within complex artificial and natural systems. Applications of cybernetic research are widespread and can be found in computer science, politics, education, ecology, psychology, management, and other disciplines. Cybernetics has not become established as an autonomous discipline because of the difficulty of maintaining coherence among some of its more specialized forms and spin-offs. There are thus few research or academic departments devoted to it.

Because of the diffuse interdisciplinarity of cybernetics, theological, religious, and philosophical concerns and engagements are multiple. Some conversations concern the social and economic impact of computer networks, such as the internet, on culture and nature. Others concern the development of artificial life and artificial intelligence and its impact on how human intelligence and life is understood. Other theological and philosophical concerns of cybernetics include the shape of divine activity in the world, the "constructed" nature of knowledge and of ethical values, the boundaries between bodies and machines and the implications for creation, the promises of salvific technology, and a tendency to strive for a metanarrative or grand unifying theory.


See also Artificial Intelligence; Artificial Life; Chaos Theory; Complexity; Cyborg; Process Thought; Systems Theory


Bibliography

ashby, w. ross. an introduction to cybernetics (1956). london: chapman and hall, 1999.

hayles, n. katherine. how we became post-human: virtual bodies in cybernetics, literature, and informatics. chicago: university of chicago press, 1999.

heylighen, francis, and joslyn, cliff. "cybernetics and second-order cybernetics." in: encyclopedia of physical science and technology, 3rd edition, ed. r. a. meyers. new york: academic press, 2001.

heylighen, francis; cliff, joslyn; and turchin, v., eds.: principia cybernetica web. brussels, belgium: principia cybernetica. available from: http://pespmc1.vub.ac.be.

marion grau

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Cybernetics

CYBERNETICS

CYBERNETICS. In a groundbreaking book in 1948 the mathematician Norbert Wiener described cybernetics as "the science of control and communication in the animal and the machine." Wiener derived the term from the Greek word kybernetes (steersman). Wiener became interested in the topic of cybernetics during World War II while working with a colleague, Julian Bigelow, on improving the accuracy of a radar-guided antiaircraft gun. For several years, cybernetics greatly influenced research on artificial intelligence. Cybernetics centers on feedback mechanisms, or methods by which information on the state of an organism or machine is fed back into the organism or machine in order to direct further changes. A biological example of feedback is the way in which warm-blooded animals automatically regulate their temperatures, keeping them within a narrow range of acceptable values by using a variety of mechanisms that lose or retain heat.

By the early 2000s, cybernetics—often known as systems science—comprised a wide range of interdisciplinary research interests and applied sciences that extended well beyond Wiener's original scope of inquiry, encompassing research in such varied realms as neural networks, chaos theory, artificial intelligence, dynamical systems, and the study of other complex, adaptive systems. The field gained its unity by emphasizing the connectedness and interactions of the diverse parts of a system, in contrast to the more traditional analytic approach that focused on comprehending systems by breaking them down into their component parts.

BIBLIOGRAPHY

Wiener, Norbert. Cybernetics: or, Control and Communication in the Animal and the Machine. 2nd ed. Cambridge, Mass.: M.I.T. Press, 1961.

———. The Human Use of Human Beings: Cybernetics and Society. New York: Avon Books, 1967. The original edition was published Boston: Houghton Mifflin, 1950.

VincentKiernan/c. w.

See alsoAutomation .

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cybernetics

cybernetics [Gr.,=steersman], term coined by American mathematician Norbert Wiener to refer to the general analysis of control systems and communication systems in living organisms and machines. In cybernetics, analogies are drawn between the functioning of the brain and nervous system and the computer and other electronic systems. The science overlaps the fields of neurophysiology, information theory, computing machinery, and automation. See servomechanism.

See N. Wiener, Cybernetics (rev. ed. 1961) and The Human Use of Human Beings (1967); F. H. Fuchs, The Brain as a Computer (1973).

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cybernetics

cybernetics Study of communication and control systems in animals, organizations and machines. It makes analogies between the brain and nervous system, and computers and other electronic systems, such as the analysis of the mechanisms of feedback and data processing. A household thermostat might be compared with the body's mechanisms for temperature control and respiration. Cybernetics combines aspects of mathematics, neurophysiology, computer technology, information theory, and psychology.

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"cybernetics." World Encyclopedia. . Encyclopedia.com. 20 Aug. 2017 <http://www.encyclopedia.com>.

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cybernetics

cy·ber·net·ics / ˌsībərˈnetiks/ • pl. n. [treated as sing.] the science of communications and automatic control systems in both machines and living things. DERIVATIVES: cy·ber·net·ic adj. cy·ber·ne·ti·cian / -nəˈtishən/ n. cy·ber·net·i·cist / -ˈnetəsəst/ n.

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"cybernetics." The Oxford Pocket Dictionary of Current English. . Encyclopedia.com. 20 Aug. 2017 <http://www.encyclopedia.com>.

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cybernetics

cybernetics The study of communication among machines, animals, and men, particularly the role of feedback information in the process of control. In the social sciences, the theory links social control closely to the nature and function of communication, and has been deployed most widely in the study of formal organizations. See also PARSONS, TALCOTT; SOCIAL SYSTEM.

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cybernetics

cybernetics A discipline concerned with control and communication in animal and machine. Cybernetics attempts to build a general theory of machines independent of the material they are made from, e.g. electronic, organic, clockwork. Cybernetics draws an analogy between brains and electronic circuits. See also neural networks.

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"cybernetics." A Dictionary of Computing. . Encyclopedia.com. 20 Aug. 2017 <http://www.encyclopedia.com>.

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cybernetics

cybernetics (sy-ber-net-iks) n. the science of communication processes and automatic control systems in both machines and living things: a study linking the working of the brain and nervous system with the functioning of computers and automated feedback devices. See also bionics.

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cybernetics

cybernetics The study of communications systems and of system control in animals and machines. In the life sciences, it also includes the study of feedback controls in homoeostasis.

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cybernetics

cybernetics The study of communications systems and of system control in animals and machines. In the life sciences, it also includes the study of feedback controls in homoeostasis.

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cybernetics

cybernetics theory of control and communication in animals and machines. XX. f. Gr. kubernḗtēs steersman, f. kubernân steer, GOVERN; see -ICS.

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"cybernetics." The Concise Oxford Dictionary of English Etymology. . Encyclopedia.com. 20 Aug. 2017 <http://www.encyclopedia.com>.

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"cybernetics." The Concise Oxford Dictionary of English Etymology. . Retrieved August 20, 2017 from Encyclopedia.com: http://www.encyclopedia.com/humanities/dictionaries-thesauruses-pictures-and-press-releases/cybernetics-0