"As soon as we are convinced that all technical and non-technical feedback systems are closely related, these relationships must not be distinguished by their specific designs in anatomy or technology; on the contrary their only common characterisation is the analogy of signal flows and the dynamics of control." (Hermann Schmidt, "Regelungstechnik - die technische Aufgabe und ihre wissenschaftliche, sozialpolitische und kulturpolitische Auswirkung", Verein Deutscher Ingenieure, Zeitschrift Vol. 85 (4), 1941)
"Besides electrical engineering theory of the transmission of messages, there is a larger field [cybernetics] which includes not only the study of language but the study of messages as a means of controlling machinery and society, the development of computing machines and other such automata, certain reflections upon psychology and the nervous system, and a tentative new theory of scientific method." (Norbert Wiener, "Cybernetics", 1948)
"We have decided to call the entire field of control and communication theory, whether in the machine or in the animal, by the name Cybernetics, which we form from the Greek [...] for steersman. In choosing this term, we wish to recognize that the first significant paper on feedback mechanisms is an article on governors, which was published by Clerk Maxwell in 1868, and that governor is derived from a Latin corruption [...] We also wish to refer to the fact that the steering engines of a ship are indeed one of the earliest and best-developed forms of feedback mechanisms." (Norbert Wiener, "Cybernetics", 1948)
"It is my thesis that the physical functioning of the living individual and the operation of some of the newer communication machines are precisely parallel in their analogous attempts to control entropy through feedback. Both of them have sensory receptors as one stage of their cycle of operation: that is, in both of them there exists a special apparatus for collecting information from the outer world at low energy levels, and for making it available in the operation of the individual or of the machine. In both cases these external messages are not taken neat, but through the internal transforming powers of the apparatus, whether it be alive or dead. The information is then turned into a new form available for the further stages of performance. In both the animal and the machine this performance is made to be effective on the outer world. In both of them, their performed action on the outer world, and not merely their intended action, is reported back to the central regulatory apparatus." (Norbert Wiener, "The Human Use of Human Beings", 1950)
"The striking parallel between the economic models that are currently under discussion and some engineering systems suggests the hope that in some way the rapid progress in the development of the theory and practice of automatic control in the world of engineering may contribute to the solution of the economic problems." (Arnold Tustin, "The Mechanism of Economic Systems", 1953)
"Feedback is a method of controlling a system by reinserting into it the results of its past performance. If these results are merely used as numerical data for the criticism of the system and its regulation, we have the simple feedback of the control engineers. If, however, the information which proceeds backward from the performance is able to change the general method and pattern of performance, we have a process which may be called learning." (Norbert Wiener, 1954)
"The purpose of ‘Engineering Cybernetics’ is then to study those parts of the broad science of cybernetics which have direct engineering applications in designing controlled or guided systems. It certainly includes such topics usually treated in books on servomechanisms. But a wider range of topics is only one difference between engineering cybernetics and servomechanisms engineering. A deeper - and thus more important - difference lies in the fact that engineering cybernetics is an engineering science, while servomechanisms engineering is an engineering practice." (Qian Xuesen, "Engineering Cybernetics", 1954)
"Cybernetics might, in fact, be defined as the study of systems that are open to energy but closed to information and control-systems that are 'information-tight'." (W Ross Ashby, "An Introduction to Cybernetics", 1956)
"Systems engineering embraces every scientific and technical concept known, including economics, management, operations, maintenance, etc. It is the job of integrating an entire problem or problem to arrive at one overall answer, and the breaking down of this answer into defined units which are selected to function compatibly to achieve the specified objectives. [...] Instrument and control engineering is but one aspect of systems engineering - a vitally important and highly publicized aspect, because the ability to create automatic controls within overall systems has made it possible to achieve objectives never before attainable, While automatic controls are vital to systems which are to be controlled, every aspect of a system is essential. Systems engineering is unbiased, it demands only what is logically required. Control engineers have been the leaders in pulling together a systems approach in the various technologies." (Instrumentation Technology, 1957)
"Systems engineering is the name given to engineering activity which considers the overall behavior of a system, or more generally which considers all factors bearing on a problem, and the systems approach to control engineering problems is correspondingly that approach which examines the total dynamic behavior of an integrated system. It is concerned more with quality of performance than with sizes, capacities, or efficiencies, although in the most general sense systems engineering is concerned with overall, comprehensive appraisal." (Ernest F Johnson, "Automatic process control", 1958)
"A real system is subject to perturbations and it is never possible to control its initial state exactly. This raises the question of stability: under a slight perturbation will the system remain near the equilibrium state or not?" Joseph P LaSalle & Solomon Lefschetz, "Stability by Liapunov's Direct Method with Applications", 1961)
"[…] cybernetics studies the flow of information round a system, and the way in which this information is used by the system as a means of controlling itself: it does this for animate and inanimate systems indifferently. For cybernetics is an interdisciplinary science, owing as much to biology as to physics, as much to the study of the brain as to the study of computers, and owing also a great deal to the formal languages of science for providing tools with which the behaviour of all these systems can be objectively described." (A Stafford Beer, 1966)
"According to the science of cybernetics, which deals with the topic of control in every kind of system (mechanical, electronic, biological, human, economic, and so on), there is a natural law that governs the capacity of a control system to work. It says that the control must be capable of generating as much 'variety' as the situation to be controlled. (Anthony S Beer, "Management Science", 1968)
"In the language of cybernetics, maintaining reactions can be outlined as follows: the sensing material receives information about the external environment in the form of coded signals. This information is reprocessed and sent in the form of new signals through defined channels, or networks. This new information brings about an internal reorganization of the system which contributes to the preservation of its integrity. The mechanism which reprocesses the information is called the control system. It consists of a vast number of input and output elements, connected by channels through which the signals are transmitted. The information can be stored in a recall or memory system, which may consist of separate elements, each of which can be in one of several stable states. The particular state of the element varies, under the influence of the input signals. When a number of such elements are in certain specified states, information is, in effect, recorded in the form of a text of finite length, using an alphabet with a finite number of characters. These processes underlie contemporary electronic computing machines and are, in a number of respects, strongly analogous to biological memory systems." (Carl Sagan, "Intelligent Life in the Universe", 1966)
"Cybernetics, based upon the principle of feedback or circular causal trains providing mechanisms for goal-seeking and self-controlling behavior." (Ludwig von Bertalanffy, "General System Theory", 1968)
"In complex systems cause and effect are often not closely related in either time or space. The structure of a complex system is not a simple feedback loop where one system state dominates the behavior. The complex system has a multiplicity of interacting feedback loops. Its internal rates of flow are controlled by nonlinear relationships. The complex system is of high order, meaning that there are many system states (or levels). It usually contains positive-feedback loops describing growth processes as well as negative, goal-seeking loops. In the complex system the cause of a difficulty may lie far back in time from the symptoms, or in a completely different and remote part of the system. In fact, causes are usually found, not in prior events, but in the structure and policies of the system." (Jay Wright Forrester, "Urban dynamics", 1969)
"The structure of a complex system is not a simple feedback loop where one system state dominates the behavior. The complex system has a multiplicity of interacting feedback loops. Its internal rates of flow are controlled by non‐linear relationships. The complex system is of high order, meaning that there are many system states (or levels). It usually contains positive‐feedback loops describing growth processes as well as negative, goal‐seeking loops." (Jay F Forrester, "Urban Dynamics", 1969)
"In self-organizing systems, on the other hand, ‘control’ of the organization is typically distributed over the whole of the system. All parts contribute evenly to the resulting arrangement." (Francis Heylighen, "The Science Of Self-Organization And Adaptivity", 1970)
"In no system which shows mental characteristics can any part have unilateral control over the whole. In other words, the mental characteristics of the system are imminent, not in some part, but in the system as a whole." (Gregory Bateson, "Steps to an Ecology of Mind", 1972)
"The essence of cybernetic organizations is that they are self-controlling, self-maintaining, self-realizing. Indeed, cybernetics has been characterized as the “science of effective organization,” in just these terms. But the word “cybernetics” conjures, in the minds of an apparently great number of people, visions of computerized information networks, closed loop systems, and robotized man-surrogates, such as ‘artorgas’ and ‘cyborgs’." (Richard F Ericson, "Visions of Cybernetic Organizations", 1972)
"A person is changed by the contingencies of reinforcement under which he behaves; he does not store the contingencies. In particular, he does not store copies of the stimuli which have played a part in the contingencies. There are no 'iconic representations' in his mind; there are no 'data structures stored in his memory'; he has no 'cognitive map' of the world in which he has lived. He has simply been changed in such a way that stimuli now control particular kinds of perceptual behavior." (Burrhus F Skinner, "About behaviorism", 1974)
"The subject of study in systems theory is not a 'physical object', a chemical or social phenomenon, for example, but a 'system': a formal relationship between observed features or attributes. For conceptual reasons, the language used in describing the behavior of systems is that of information processing and goal seeking (decision making control)." (Mihajlo D Mesarovic & Y Takahara, "Foundations for the mathematical theory of general systems", 1975)
"The treatment of the economy as a single system, to be controlled toward a consistent goal, allowed the efficient systematization of enormous information material, its deep analysis for valid decision-making. It is interesting that many inferences remain valid even in cases when this consistent goal could not be formulated, either for the reason that it was not quite clear or for the reason that it was made up of multiple goals, each of which to be taken into account." (Leonid V Kantorovich, "Mathematics in Economics: Achievements, Difficulties, Perspectives", [Nobel lecture] 1975)
"Effect spreads its 'tentacles' not only forwards (as a new cause giving rise to a new effect) but also backwards, to the cause which gave rise to it, thus modifying, exhausting or intensifying its force. This interaction of cause and effect is known as the principle of feedback. It operates everywhere, particularly in all self-organising systems where perception, storing, processing and use of information take place, as for example, in the organism, in a cybernetic device, and in society. The stability, control and progress of a system are inconceivable without feedback." (Alexander Spirkin, "Dialectical Materialism", 1983)
"The autonomy of living systems is characterized by closed, recursive organization. [...] A system's highest order of recursion or feedback process defines, generates, and maintains the autonomy of a system. The range of deviation this feedback seeks to control concerns the organization of the whole system itself. If the system should move beyond the limits of its own range of organization it would cease to be a system. Thus, autonomy refers to the maintenance of a systems wholeness. In biology, it becomes a definition of what maintains the variable called living." (Bradford P Keeney, "Aesthetics of Change", 1983)
"The emphasis in system(s) theory is on the dynamic behaviour of these phenomena, i.e. how do characteristic features (such as input and output) change in time and what are the relationships, also as functions of time. One tries to design control systems such that a desired behaviour is achieved. In this sense mathematical system(s) theory (and control theory) distinguishes itself from many other branches of mathematics in the sense that it is prescriptive rather than descriptive." (G J Olsder & J.W. van der Woude, "Mathematical Systems Theory" 2nd Ed., 1983)
"Ultimately, uncontrolled escalation destroys a system. However, change in the direction of learning, adaptation, and evolution arises from the control of control, rather than unchecked change per se. In general, for the survival and co-evolution of any ecology of systems, feedback processes must be embodied by a recursive hierarchy of control circuits." (Bradford P Keeney, "Aesthetics of Change", 1983)
"What is sometimes called 'positive feedback' or 'amplified deviation' is therefore a partial arc or sequence of a more encompassing negative feedback process. The appearance of escalating runaways in systems is a consequence of the frame of reference an observer has punctuated. Enlarging one's frame of reference enables the 'runaway' to be seen as a variation subject to higher orders of control." (Bradford P Keeney, "Aesthetics of Change", 1983)
"Conversely, once it was realized that the concept of policy was fundamental in control theory, the mathematicization of the basic engineering concept of 'feedback control', then the emphasis upon a state variable formulation became natural. We see then a very interesting interaction between dynamic programming and control theory. This reinforces the point that when working in the field of analysis it is exceedingly helpful to have some underlying physical processes clearly in mind." (Richard E Bellman, "Eye of the Hurricane: An Autobiography", 1984)
"Stability theory is the study of systems under various perturbing influences. Since there are many systems, many types of influences, and many equations describing systems, this is an open-ended problem. A system is designed so that it will be stable under external influences. However, one cannot predict all external influences, nor predict the magnitude of those that occur. Consequently, we need control theory. If one is interested in stability theory, a natural result is a theory of control." (Richard E Bellman, "Eye of the Hurricane: An Autobiography", 1984)
"The term closed loop-learning process refers to the idea that one learns by determining what s desired and comparing what is actually taking place as measured at the process and feedback for comparison. The difference between what is desired and what is taking place provides an error indication which is used to develop a signal to the process being controlled." (Harold Chestnut, 1984)
"Perhaps the most exciting implication [of CA representation of biological phenomena] is the possibility that life had its origin in the vicinity of a phase transition and that evolution reflects the process by which life has gained local control over a successively greater number of environmental parameters affecting its ability to maintain itself at a critical balance point between order and chaos." ( Chris G Langton, "Computation at the Edge of Chaos: Phase Transitions and Emergent Computation", Physica D (42), 1990)
"There must be, however, cybernetic or homeostatic mechanisms for preventing the overall variables of the social system from going beyond a certain range. There must, for instance, be machinery for controlling the total numbers of the population; there must be machinery for controlling conflict processes and for preventing perverse social dynamic processes of escalation and inflation. One of the major problems of social science is how to devise institutions which will combine this overall homeostatic control with individual freedom and mobility." (Kenneth Boulding, "Economics of the coming spaceship Earth", 1994)
"The internet model has many lessons for the new economy but perhaps the most important is its embrace of dumb swarm power. The aim of swarm power is superior performance in a turbulent environment. When things happen fast and furious, they tend to route around central control. By interlinking many simple parts into a loose confederation, control devolves from the center to the lowest or outermost points, which collectively keep things on course. A successful system, though, requires more than simply relinquishing control completely to the networked mob." (Kevin Kelly, "New Rules for the New Economy: 10 radical strategies for a connected world", 1998)
"When everything is connected to everything in a distributed network, everything happens at once. When everything happens at once, wide and fast moving problems simply route around any central authority. Therefore overall governance must arise from the most humble interdependent acts done locally in parallel, and not from a central command.A mob can steer itself, and in the territory of rapid, massive, and heterogeneous change, only a mob can steer. To get something from nothing, control must rest at the bottom within simplicity. " (Kevin Kelly, "Out of Control: The New Biology of Machines, Social Systems and the Economic World", 1995)
"At present, there is far more to be gained by pushing the boundaries of what can be done by the bottom than by focusing on what can be done at the top. When it comes to control, there is plenty of room at the bottom. What we are discovering is that peer-based networks with millions of parts, minimal oversight, and maximum connection among them can do far more than anyone ever expected. We don’t yet know what the limits of decentralization are." (Kevin Kelly, "New Rules for the New Economy: 10 radical strategies for a connected world", 1998)
"Complexity theory began with an interest on how order spring from chaos. According to complexity theory, adaption is most effective in systems that are only partially connected. The argument is that too much structure creates gridlock, while too little structure creates chaos. […] Consequently, the key to effective change is to stay poised on this edge of chaos. Complexity theory focuses managerial thinking on the interrelationships among different parts of an organization and on the trade-off of less control for greater adaptation." (Shona Brown, "Competing on the Edge, 1998)
"A model is an external and explicit representation of part of reality as seen by the people who wish to use that model to understand, to change, to manage, and to control that part of reality in some way or other." (Michael Pidd, "Just Modeling through: A Rough Guide to Modeling", Interfaces, Vol. 29, No. 2, 1999)
"Cybernetics is the science of effective organization, of control and communication in animals and machines. It is the art of steersmanship, of regulation and stability. The concern here is with function, not construction, in providing regular and reproducible behaviour in the presence of disturbances. Here the emphasis is on families of solutions, ways of arranging matters that can apply to all forms of systems, whatever the material or design employed. [...] This science concerns the effects of inputs on outputs, but in the sense that the output state is desired to be constant or predictable – we wish the system to maintain an equilibrium state. It is applicable mostly to complex systems and to coupled systems, and uses the concepts of feedback and transformations (mappings from input to output) to effect the desired invariance or stability in the result." (Chris Lucas, "Cybernetics and Stochastic Systems", 1999)
"The central proposition in [realistic thinking] is that human actions and interactions are processes, not systems, and the coherent patterning of those processes becomes what it becomes because of their intrinsic capacity, the intrinsic capacity of interaction and relationship, to form coherence. That emergent form is radically unpredictable, but it emerges in a controlled or patterned way because of the characteristic of relationship itself, creation and destruction in conditions at the edge of chaos." (Ralph D Stacey et al, "Complexity and Management: Fad or Radical Challenge to Systems Thinking?", 2000)
"A model is an imitation of reality and a mathematical model is a particular form of representation. We should never forget this and get so distracted by the model that we forget the real application which is driving the modelling. In the process of model building we are translating our real world problem into an equivalent mathematical problem which we solve and then attempt to interpret. We do this to gain insight into the original real world situation or to use the model for control, optimization or possibly safety studies." (Ian T Cameron & Katalin Hangos, "Process Modelling and Model Analysis", 2001)
"Probably the first clear insight into the deep nature of control […] was that it is not about pulling levers to produce intended and inexorable results. This notion of control applies only to trivial machines. It never applies to a total system that includes any kind of probabilistic element - from the weather, to people; from markets, to the political economy. No: the characteristic of a non-trivial system that is under control, is that despite dealing with variables too many to count, too uncertain to express, and too difficult even to understand, something can be done to generate a predictable goal. Wiener found just the word he wanted in the operation of the long ships of ancient Greece. At sea, the long ships battled with rain, wind and tides - matters in no way predictable. However, if the man operating the rudder kept his eye on a distant lighthouse, he could manipulate the tiller, adjusting continuously in real-time towards the light. This is the function of steersmanship. As far back as Homer, the Greek word for steersman was kubernetes, which transliterates into English as cybernetes." (Stafford Beer, "What is cybernetics?", Kybernetes, 2002)
"We’re accustomed to thinking in terms of centralized control, clear chains of command, the straightforward logic of cause and effect. But in huge, interconnected systems, where every player ultimately affects every other, our standard ways of thinking fall apart. Simple pictures and verbal arguments are too feeble, too myopic." (Steven Strogatz, "Sync: The Emerging Science of Spontaneous Order", 2003)
"Feedback and its big brother, control theory, are such important concepts that it is odd that they usually find no formal place in the education of physicists. On the practical side, experimentalists often need to use feedback. Almost any experiment is subject to the vagaries of environmental perturbations. Usually, one wants to vary a parameter of interest while holding all others constant. How to do this properly is the subject of control theory. More fundamentally, feedback is one of the great ideas developed (mostly) in the last century, with particularly deep consequences for biological systems, and all physicists should have some understanding of such a basic concept." (John Bechhoefer, "Feedback for physicists: A tutorial essay on control", Reviews of Modern Physics Vol. 77, 2005)
"The science of cybernetics is not about thermostats or machines; that characterization is a caricature. Cybernetics is about purposiveness, goals, information flows, decision-making control processes and feedback (properly defined) at all levels of living systems." (Peter Corning, "Synergy, Cybernetics, and the Evolution of Politics", 2005)
"The single most important property of a cybernetic system is that it is controlled by the relationship between endogenous goals and the external environment. [...] In a complex system, overarching goals may be maintained (or attained) by means of an array of hierarchically organized subgoals that may be pursued contemporaneously, cyclically, or seriatim." (Peter Corning, "Synergy, Cybernetics, and the Evolution of Politics", 2005)
"A great deal of the results in many areas of physics are presented in the form of conservation laws, stating that some quantities do not change during evolution of the system. However, the formulations in cybernetical physics are different. Since the results in cybernetical physics establish how the evolution of the system can be changed by control, they should be formulated as transformation laws, specifying the classes of changes in the evolution of the system attainable by control function from the given class, i.e., specifying the limits of control." (Alexander L Fradkov, "Cybernetical Physics: From Control of Chaos to Quantum Control", 2007)
"To develop a Control, the designer should find aspect systems, subsystems, or constraints that will prevent the negative interferences between elements (friction) and promote positive interferences (synergy). In other words, the designer should search for ways of minimizing frictions that will result in maximization of the global satisfaction" (Carlos Gershenson, "Design and Control of Self-organizing Systems", 2007)
"[a complex system is] a system in which large networks of components with no central control and simple rules of operation give rise to complex collective behavior, sophisticated information processing, and adaptation via learning or evolution." (Melanie Mitchell, "Complexity: A Guided Tour", 2009)
"[…] in cybernetics, control is seen not as a function of one agent over something else, but as residing within circular causal networks, maintaining stabilities in a system. Circularities have no beginning, no end and no asymmetries. The control metaphor of communication, by contrast, punctuates this circularity unevenly. It privileges the conceptions and actions of a designated controller by distinguishing between messages sent in order to cause desired effects and feedback that informs the controller of successes or failures." (Klaus Krippendorff, "On Communicating: Otherness, Meaning, and Information", 2009)
"In a complex society, individuals, organizations, and states require a high degree of confidence - even if it is misplaced - in the short-term future and a reasonable degree of confidence about the longer term. In its absence they could not commit themselves to decisions, investments, and policies. Like nudging the frame of a pinball machine to influence the path of the ball, we cope with the dilemma of uncertainty by doing what we can to make our expectations of the future self-fulfilling. We seek to control the social and physical worlds not only to make them more predictable but to reduce the likelihood of disruptive and damaging shocks (e.g., floods, epidemics, stock market crashes, foreign attacks). Our fallback strategy is denial." (Richard N Lebow, "Forbidden Fruit: Counterfactuals and International Relations", 2010)
"In chaotic deterministic systems, the probabilistic description is not linked to the number of degrees of freedom (which can be just one as for the logistic map) but stems from the intrinsic erraticism of chaotic trajectories and the exponential amplification of small uncertainties, reducing the control on the system behavior." (Massimo Cencini et al, "Chaos: From Simple Models to Complex Systems", 2010)
"Cyberneticists argue that positive feedback may be useful, but it is inherently unstable, capable of causing loss of control and runaway. A higher level of control must therefore be imposed upon any positive feedback mechanism: self-stabilising properties of a negative feedback loop constrain the explosive tendencies of positive feedback. This is the starting point of our journey to explore the role of cybernetics in the control of biological growth. That is the assumption that the evolution of self-limitation has been an absolute necessity for life forms with exponential growth." (Tony Stebbing, "A Cybernetic View of Biological Growth: The Maia Hypothesis", 2011)
"Cybernetics is the study of systems which can be mapped using loops (or more complicated looping structures) in the network defining the flow of information. Systems of automatic control will of necessity use at least one loop of information flow providing feedback." (Alan Scrivener, "A Curriculum for Cybernetics and Systems Theory", 2012)
"Without precise predictability, control is impotent and almost meaningless. In other words, the lesser the predictability, the harder the entity or system is to control, and vice versa. If our universe actually operated on linear causality, with no surprises, uncertainty, or abrupt changes, all future events would be absolutely predictable in a sort of waveless orderliness." (Lawrence K Samuels, "Defense of Chaos: The Chaology of Politics, Economics and Human Action", 2013)
[systems dynamics:] "A systems simulation methodology to study complex dynamic behavior of industrial and social systems based on control engineering and cybernetics." (Michael Mutingi & Charles Mbohwa, 2014)
"The problem of complexity is at the heart of mankind’s inability to predict future events with any accuracy. Complexity science has demonstrated that the more factors found within a complex system, the more chances of unpredictable behavior. And without predictability, any meaningful control is nearly impossible. Obviously, this means that you cannot control what you cannot predict. The ability ever to predict long-term events is a pipedream. Mankind has little to do with changing climate; complexity does." (Lawrence K Samuels, "The Real Science Behind Changing Climate", 2014)
"Cybernetics studies the concepts of control and communication in living organisms, machines and organizations including self-organization. It focuses on how a (digital, mechanical or biological) system processes information, responds to it and changes or being changed for better functioning (including control and communication)." (Dmitry A Novikov, "Cybernetics 2.0", 2016)
