A Stafford Beer - Collected Quotes

"A deterministic system is one in which the parts interact in a perfectly predictable way. There is never any room for doubt: given a last state of the system and the programme of information by defining its dynamic network, it is always possible to predict, without any risk of error, its succeeding state. A probabilistic system, on the other hand, is one about which no precisely detailed prediction can be given. The system may be studied intently, and it may become more and more possible to say what it is likely to do in any given circumstances. But the system simply is not predetermined, and a prediction affecting it can never escape from the logical limitations of the probabilities in which terms alone its behaviour can be described." (Stafford Beer, "Cybernetics and Management", 1959)

"But in addition to what we decide to do by way of transformation, there are certain tendencies in the way systems behave of their own volition when left to their own devices. The convenient analogy for one of these processes is found in the second law of thermodynamics: an 'ordering' process goes on, for which the name is entropy. This can be explained without technicalities as the tendency of a system to settle down to a uniform distribution of its energy. The dissipation of local pockets of high energy is measured by an increase in entropy, until at maximum entropy all is uniform. According to this model, order is more 'natural' than chaos. This is the reason why it is convenient to discuss cybernetic systems, with their self-regulating tendency to attain stability or orderliness, in terms of entropy - a term which has been taken over to name a key tool of cybernetics." (Stafford Beer, "Cybernetics and Management", 1959)

"Control is an attribute of a system. This word is not used in the way in which either an office manager or a gambler might use it; it is used as a name for connectiveness. That is, anything that consists of parts connected together will be called a system." (Stafford Beer, "Cybernetics and Management", 1959)

"A system in a dynamic state, that is to say, one which is operating, may pass quite rapidly from one state to another for an indefinite period, and accounting for this behaviour will obviously require a vast investigation." (Stafford Beer, "Cybernetics and Management", 1959)

"If a machine is a purposive system, then the machine's description will be given by an account of the successive states of the system as its purpose unfolds. This succession of states is given by a set of transitions of one item to another, and this set is known technically as a transformation. When the transforms obtained from a transformation include no fresh item, but are concerned with re-arranging the items that are there already, we speak of a closed system." (Stafford Beer, "Cybernetics and Management", 1959)

"It will be useful if we base the arbitrary classification of systems on two distinct criteria. One obviously valuable criterion is that of the system's complexity. Adopting this criterion, it will be possible to discuss systems according to a three-fold scheme. The least complex with which we shall be concerned may be called: simple but dynamic. A system which is not simple, but which has become highly elaborate and is richly interconnected, will be called: complex but describable. Thirdly, we may discuss systems which have be- come so complicated that, while they may still be designated as complex, they cannot be described in a precise and detailed fashion. Such systems will be called: exceedingly complex." (Stafford Beer, "Cybernetics and Management", 1959)

"There are many kinds of effective control inside deterministic systems, and feedback is only one of them. The most reliable control method is, after all, direct coupling - which can be used in the absence of natural variation in what is connected. In the probabilistic category, however, feedback offers the only really effective mechanism for controlling endemic variation." (Stafford Beer, "Cybernetics and Management", 1959)

"[...] there can be such a thing as a simple probabilistic system. For example, consider the tossing of a penny. Here is a perfectly simple system, but one which is notoriously unpredictable. It maybe described in terms of a binary decision process, with a built-in even probability between the two possible outcomes." (Stafford Beer, "Cybernetics and Management", 1959)

"[…] 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)

"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)

"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) 

"The shocking thing is that there is truth in every one of these notions, and the reason is because cybernetics is an interdisciplinary subject. It must be complicated." (Stafford Beer, "What is cybernetics?", Kybernetes, 2002)

Dmitry A Novikov - Collected Quotes

"A law is a permanent cause-and-effect relation of phenomena or processes. A law is a necessary, essential, stable and repetitive relation among phenomena." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

"A theory is an organizational form of scientific knowledge about a certain set of objects, representing a system of interconnected assertions and proofs and containing methods of explanation and prediction of phenomena and processes in a given problem domain, i.e., of all phenomena and processes described by this theory." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

"Cybernetics is an interdisciplinary science. It originated ‘at the junction’ of mathematics, logic, semiotics, physiology, biology and sociology. Among its inherent features, we mention analysis and revelation of general principles and approaches in scientific cognition. Control theory, communication theory, operations research and others represent most weighty theories within cybernetics 1.0." (Dmitry A Novikov, "Cybernetics 2.0", 2016)

"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: From Past to Future", 2016)

"The principle of reactions - responding to an external influence, a system reinforces processes to compensate it (the Le Chatelier–Brown principle imported from physics and chemistry)." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

"The principle of system cohesion - a system’s form is maintained by a balance, static or dynamic, between cohesive and dispersive influences. The form of an interacting set of systems is similarly maintained." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

"The principle of adaptation - for continued system cohesion, the mean rate of system adaptation must equal or exceed the mean rate of changes of environment (the response times obey the reverse rule)." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

"The principle of connected variety - interacting systems stability increases with variety, and with the degree of connectivity of that variety within the environment." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

"The principle of limited variety - variety in interacting systems is limited by the available space and the minimum degree of differentiation." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

"The principle of preferred pattern - the probability that interacting systems will adopt locally-stable configurations increases both with the variety of systems and with their connectivity." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

"The principle of cyclic progression - interconnected systems driven by an external energy source will tend to a cyclic progression in which system variety is generated, dominance emerges to suppress the variety, the dominant mode decays or collapses, and survivors emerge to regenerative variety." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of hierarchy:] "Generally, a control system has a hierarchical structure. It must agree with the functional structure of a controlled system and not contradict the hierarchy of (horizontally or vertically) adjacent systems. Tasks and resources supporting the activity of a controlled system must be decomposed according to its structure." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of unification:] "Controlled systems and control systems of all levels must be described and studied using common principles (this applies both to the parameters of their models and the efficiency criteria of their functioning). However, such principles must not eliminate the necessity of considering the specifics of a concrete system. Most real control situations can be reduced to a set of the so-called typical situations, where the corresponding typical decisions appear optimal. On the other part, control inevitably causes specialization (restriction of variety) of control subjects and controlled subjects." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of purposefulness:] "Any impact of a control system on a controlled system must be purposeful." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of openness:] "Operation of a control system must be open to information, innovations, etc." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of efficiency:] "A control system must implement the most efficient control actions from the set of feasible control actions (also see the principle of extremization)." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of responsibility:] "A control system appears responsible for decisions made and the efficiency of controlled system operation." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of non-interference:] "Any-level Principal interferes in a process iff its direct subordinates are unable to implement a complex of necessary functions (at present and/or based on a forecast)." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of social and state control, participation:] "Control of a social system must aim at the maximal involvement of all interested subjects (society, bodies of state power, individual and artificial persons) in the development of a controlled system and its operation."(Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of development:] "A control action lies in modifying a control system proper (being induced from within, it can be treated as self-development). The matter also concerns the development of a controlled system."(Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of completeness and prediction): "Under a given range of external conditions, the set of control actions must ensure posed goals (the completeness requirement) in an optimal and/or feasible way. This must be done taking into account a possible response of a controlled system to certain control actions in predicted external conditions." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of regulation and resource provision:] "Control activity must be regulated (standardized) and correspond to constraints set by a metasystem (a system possessing a higher hierarchical level). Any management decision or control action must be feasible (also, in the sense of provision with necessary resources)."(Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of feedback:] "Efficient control generally requires information on the state of a controlled system and on the conditions of its functioning. Moreover, implementation of a control action and corresponding consequences must be monitored by a control subject." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of adequacy:] "A control system (its structure, complexity, functions) must be adequate to a controlled system (to its structure, complexity, functions, respectively). Problems to-be-solved by a controlled system must be adequate to its capabilities." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of well-timed control:] "This principle states that, in real-time control, information required for decision-making must be supplied at the right time. Moreover, management decisions (control actions) must be made and implemented (chosen and generated, respectively) quickly enough according to any changes in a controlled system and external conditions of its functioning. In other words, the characteristic time of management decisions or control actions must not exceed the characteristic time of changes in a controlled system (i.e., a control system must be adequate to controlled processes in the sense of their rate of change)." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[principle of predictive reflection:] "A complex adaptive system predicts feasible changes in essential external parameters. Consequently, when generating control actions, one should predict and anticipate such changes." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of adaptivity:] "The principle of predictive reflection underlines the necessity of predicting the states of a controlled system and corresponding actions of a Principal. In contrast, the principle of adaptivity states that (1) one must consider all available information on the history of controlled system functioning and (2) once made decisions or chosen control actions (and the corresponding principles of decision-making) must be regularly revised (see the principle of well-timed control) following any changes in the states of a controlled system and in the conditions of its functioning." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of rational decentralization:] "This principle claims that, in any complex multi-level system, there exists a rational decentralization level for control, authorities, responsibility, awareness, resources, etc. Rational decentralization implies adequate decomposition and aggregation of goals, problems, functions, resources, and so on." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of democratic control aka anonymity:] "This principle requires equal conditions and opportunities for all participants of a controlled system (without a priori discrimination in informational, material, financial, educational and other resources)." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of coordination:] "This principle declares that, under existing institutional constraints, control actions must be maximally coordinated with the interests and preferences of controlled subjects." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

[the principle of ethics, the principle of humanism] "implies that, in management and control, consideration of existing ethical norms (in a society or an organization) has a higher priority over other criteria." (Dmitry A Novikov, "Cybernetics: From Past to Future", 2016)

Alexander L Fradkov - Collected Quotes

"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)

"A typical control goal when controlling chaotic systems is to transform a chaotic trajectory into a periodic one. In terms of control theory it means stabilization of an unstable periodic orbit or equilibrium. A specific feature of this problem is the possibility of achieving the goal by means of an arbitrarily small control action. Other control goals like synchronization and chaotization can also be achieved by small control in many cases." (Alexander L Fradkov, "Cybernetical Physics: From Control of Chaos to Quantum Control", 2007)

"Chaotic system is a deterministic dynamical system exhibiting irregular, seemingly random behavior. Two trajectories of a chaotic system starting close to each other will diverge after some time (such an unstable behavior is often called 'sensitive dependence on initial conditions'). Mathematically, chaotic systems are characterized by local instability and global boundedness of the trajectories. Since local instability of a linear system implies unboundedness (infinite growth) of its solutions, chaotic system should be necessarily nonlinear, i.e., should be described by a nonlinear mathematical model." (Alexander L Fradkov, "Cybernetical Physics: From Control of Chaos to Quantum Control", 2007)

"Systematic usage of the methods of modern control theory to study physical systems is a key feature of a new research area in physics that may be called cybernetical physics. The subject of cybernetical physics is focused on studying physical systems by means of feedback interactions with the environment. Its methodology heavily relies on the design methods developed in cybernetics. However, the approach of cybernetical physics differs from the conventional use of feedback in control applications (e.g., robotics, mechatronics) aimed mainly at driving a system to a prespecified position or a given trajectory." (Alexander L Fradkov, "Cybernetical Physics: From Control of Chaos to Quantum Control", 2007)

"The methodology of feedback design is borrowed from cybernetics (control theory). It is based upon methods of controlled system model’s building, methods of system states and parameters estimation (identification), and methods of feedback synthesis. The models of controlled system used in cybernetics differ from conventional models of physics and mechanics in that they have explicitly specified inputs and outputs. Unlike conventional physics results, often formulated as conservation laws, the results of cybernetical physics are formulated in the form of transformation laws, establishing the possibilities and limits of changing properties of a physical system by means of control." (Alexander L Fradkov, "Cybernetical Physics: From Control of Chaos to Quantum Control", 2007)

"The term synchronization in scientific colloquial use means coordination or agreement in time of two or several processes or objects. For example, it may be coincidence or closeness of the observable variables for two or several systems. Synchronization may also manifest itself as correlated in time changes of some quantitative characteristics of the systems." (Alexander L Fradkov, "Cybernetical Physics: From Control of Chaos to Quantum Control", 2007)

Out of Context: On Cybernetics (Definitions)

"Cybernetics is a word invented to define a new field in science. It combines under one heading the study of what in a human context is sometimes loosely described as thinking and in engineering is known as control and communication. In other words, cybernetics attempts to find the common elements in the functioning of automatic machines and of the human nervous system, and to develop a theory which will cover the entire field of control and communication in machines and in living organisms." (Norbert Wiener, "Cybernetics", 1948)

"Cybernetics is similar in its relation to the actual machine. It takes as its subject-matter the domain of 'all possible machines', and is only secondarily interested if informed that some of them have not yet been made, either by Man or by Nature."(W Ross Ashby, "An Introduction to Cybernetics", 1956)

"[Cybernetics is] the art of ensuring the efficacy of action." (Louis Couffignal, 1958)

"Cybernetics is the science of the process of transmission, processing and storage of information." (Sergei Sobolew, Woprosy Psychology, 1958)

"Cybernetics is the general science of communication. But to refer to communication is consciously or otherwise to refer to distinguishable states of information inputs and outputs and /or to information being processed within some relatively isolated system." (Henryk Greniewski, "Cybernetics without Mathematics", 1960)

"Cybernetics is concerned primarily with the construction of theories and models in science, without making a hard and fast distinction between the physical and the biological sciences." (Frank H George, "The Brain As A Computer", 1962)

"Cybernetics is the science or the art of manipulating defensible metaphors; showing how they may be constructed and what can be inferred as a result of their existence." (Gordon Pask, "The Cybernetics of Human Performance and Learning", 1966)

"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)

"Cybernetics is a homogenous and coherent scientific complex, a science resulting from the blending of at least two sciences - psychology and technology; it is a general and integrative science, a crossroads of sciences, involving both animal and car psychology. It is not just a discipline, circumscribed in a narrow and strictly defined field, but a complex of disciplines born of psychology and centered on it, branched out as branches of a tree in its stem. It is a stepwise synthesis, a suite of multiple, often reciprocal, modeling; syntheses and modeling in which, as a priority, and as a great importance, the modeling of psychology on the technique and then the modeling of the technique on psychology. Cybernetics is an intellectual symphony, a symphony of ideas and sciences." (Stefan Odobleja, 1978)

"Cybernetics is concerned with scientific investigation of systemic processes of a highly varied nature, including such phenomena as regulation, information processing, information storage, adaptation, self-organization, self-reproduction, and strategic behavior." (Fritz B Simon et al, "Language of Family Therapy: A Systemic Vocabulary and Source Book", 1985)

"It seems that cybernetics is many different things to many different people. But this is because of the richness of its conceptual base; and I believe that this is very good, otherwise cybernetics would become a somewhat boring exercise. However, all of those perspectives arise from one central theme; that of circularity." (Heinz von Foerster, "Ethics and Second-Order Cybernetics", 1991)

"Cybernetics is a science of purposeful behavior. It helps us explain behavior as the continuous action of someone (or thing) in the process, as we see it, of maintaining certain conditions near a goal state, or purpose." (Jeff Dooley, "Thoughts on the Question: What is Cybernetics", 1995)

"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." (Chris Lucas, "Cybernetics and Stochastic Systems", 1999)

"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)

"Cybernetics is the study of systems and processes that interact with themselves and produce themselves from themselves." (Louis Kauffman, 2007)

"Cybernetics is the art of creating equilibrium in a world of possibilities and constraints. This is not just a romantic description, it portrays the new way of thinking quite accurately." (Ernst von Glasersfeld, "Partial Memories: Sketches from an Improbable Life", 2010)

"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." (Alan Scrivener, "A Curriculum for Cybernetics and Systems Theory", 2012)

Complex Systems I

"The complexity of a system is no guarantee of its accuracy." (John P Jordan, "Cost accounting; principles and practice", 1920)

"[…] to the scientific mind the living and the non-living form one continuous series of systems of differing degrees of complexity […], while to the philosophic mind the whole universe, itself perhaps an organism, is composed of a vast number of interlacing organisms of all sizes." (James G Needham, "Developments in Philosophy of Biology", Quarterly Review of Biology Vol. 3 (1), 1928)

"A material model is the representation of a complex system by a system which is assumed simpler and which is also assumed to have some properties similar to those selected for study in the original complex system. A formal model is a symbolic assertion in logical terms of an idealised relatively simple situation sharing the structural properties of the original factual system." (Arturo Rosenblueth & Norbert Wiener, "The Role of Models in Science", Philosophy of Science Vol. 12 (4), 1945)

"[Disorganized complexity] is a problem in which the number of variables is very large, and one in which each of the many variables has a behavior which is individually erratic, or perhaps totally unknown. However, in spite of this helter-skelter, or unknown, behavior of all the individual variables, the system as a whole possesses certain orderly and analyzable average properties. [...] [Organized complexity is] not problems of disorganized complexity, to which statistical methods hold the key. They are all problems which involve dealing simultaneously with a sizable number of factors which are interrelated into an organic whole. They are all, in the language here proposed, problems of organized complexity." (Warren Weaver, "Science and Complexity", American Scientist Vol. 36, 1948)

"Cybernetics is likely to reveal a great number of interesting and suggestive parallelisms between machine and brain and society. And it can provide the common language by which discoveries in one branch can readily be made use of in the others. [...] [There are] two peculiar scientific virtues of cybernetics that are worth explicit mention. One is that it offers a single vocabulary and a single set of concepts suitable for representing the most diverse types of system. [...] The second peculiar virtue of cybernetics is that it offers a method for the scientific treatment of the system in which complexity is outstanding and too important to be ignored. Such systems are, as we well know, only too common in the biological world!" (W Ross Ashby, "An Introduction to Cybernetics", 1956)

"In the simpler systems, the methods of cybernetics sometimes show no obvious advantage over those that have long been known. It is chiefly when the systems become complex that the new methods reveal their power." (W Ross Ashby, "An Introduction to Cybernetics", 1956)

"Roughly, by a complex system I mean one made up of a large number of parts that interact in a nonsimple way. In such systems, the whole is more than the sum of the parts, not in an ultimate, metaphysical sense, but in the important pragmatic sense that, given the properties of the parts and the laws of their interaction, it is not a trivial matter to infer the properties of the whole." (Herbert A Simon, "The Architecture of Complexity", Proceedings of the American Philosophical Society, Vol. 106 (6), 1962)

"A more viable model, one much more faithful to the kind of system that society is more and more recognized to be, is in process of developing out of, or is in keeping with, the modern systems perspective (which we use loosely here to refer to general systems research, cybernetics, information and communication theory, and related fields). Society, or the sociocultural system, is not, then, principally an equilibrium system or a homeostatic system, but what we shall simply refer to as a complex adaptive system." (Walter F Buckley, "Society as a complex adaptive system", 1968)

On Automata I

"Ninety-nine [students] out of a hundred are automata, careful to walk in prescribed paths, careful to follow the prescribed custom. This is not an accident but the result of substantial education, which, scientifically defined, is the subsumption of the individual." (William T Harris, "The Philosophy of Education", 1889)

"We are automata entirely controlled by the forces of the medium being tossed about like corks on the surface of the water, but mistaking the resultant of the impulses from the outside for free will. The movements and other actions we perform are always life preservative and tho seemingly quite independent from one another, we are connected by invisible links." (Nikola Tesla, "My Inventions", 1919)

"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)

"Automata have begun to invade certain parts of mathematics too, particularly but not exclusively mathematical physics or applied mathematics. The natural systems (e.g., central nervous system) are of enormous complexity and it is clearly necessary first to subdivide what they represent into several parts that to a certain extent are independent, elementary units. The problem then consists of understanding how these elements are organized as a whole. It is the latter problem which is likely to attract those who have the background and tastes of the mathematician or a logician. With this attitude, he will be inclined to forget the origins and then, after the process of axiomatization is complete, concentrate on the mathematical aspects." (John Von Neumann, "The General and Logical Theory of Automata", 1951)

"A world of automata – of creatures that worked like machines – would hardly be worth creating." (Clive S Lewis, Mere Christianity, 1952)

"Cellular automata are discrete dynamical systems with simple construction but complex self-organizing behaviour. Evidence is presented that all one-dimensional cellular automata fall into four distinct universality classes. Characterizations of the structures generated in these classes are discussed. Three classes exhibit behaviour analogous to limit points, limit cycles and chaotic attractors. The fourth class is probably capable of universal computation, so that properties of its infinite time behaviour are undecidable." (Stephen Wolfram, "Nonlinear Phenomena, Universality and complexity in cellular automata", Physica 10D, 1984)

"Cellular automata are mathematical models for complex natural systems containing large numbers of simple identical components with local interactions. They consist of a lattice of sites, each with a finite set of possible values. The value of the sites evolve synchronously in discrete time steps according to identical rules. The value of a particular site is determined by the previous values of a neighbourhood of sites around it." (Stephen Wolfram, "Nonlinear Phenomena, Universality and complexity in cellular automata", Physica 10D, 1984)

"Cellular automata may be considered as discrete dynamical systems. In almost all cases, cellular automaton evolution is irreversible. Trajectories in the configuration space for cellular automata therefore merge with time, and after many time steps, trajectories starting from almost all initial states become concentrated onto 'attractors'. These attractors typically contain only a very small fraction of possible states. Evolution to attractors from arbitrary initial states allows for 'self-organizing' behaviour, in which structure may evolve at large times from structureless initial states. The nature of the attractors determines the form and extent of such structures." (Stephen Wolfram, "Nonlinear Phenomena, Universality and complexity in cellular automata", Physica 10D, 1984)

"Finite Nature is a hypothesis that ultimately every quantity of physics, including space and time, will turn out to be discrete and finite; that the amount of information in any small volume of space-time will be finite and equal to one of a small number of possibilities. [...] We take the position that Finite Nature implies that the basic substrate of physics operates in a manner similar to the workings of certain specialized computers called cellular automata." (Edward Fredkin, "A New Cosmogony", PhysComp ’92: Proceedings of the Workshop on Physics and Computation, 1993)

Information Theory I

"Cybernetics is concerned primarily with the construction of theories and models in science, without making a hard and fast distinction between the physical and the biological sciences. The theories and models occur both in symbols and in hardware, and by 'hardware’ we shall mean a machine or computer built in terms of physical or chemical, or indeed any handleable parts. Most usually we shall think of hardware as meaning electronic parts such as valves and relays. Cybernetics insists, also, on a further and rather special condition that distinguishes it from ordinary scientific theorizing: it demands a certain standard of effectiveness. In this respect it has acquired some of the same motive power that has driven research on modern logic, and this is especially true in the construction and application of artificial languages and the use of operational definitions. Always the search is for precision and effectiveness, and we must now discuss the question of effectiveness in some detail. It should be noted that when we talk in these terms we are giving pride of place to the theory of automata at the expense, at least to some extent, of feedback and information theory." (Frank H George, "The Brain As A Computer", 1962)

"The general notion in communication theory is that of information. In many cases, the flow of information corresponds to a flow of energy, e. g. if light waves emitted by some objects reach the eye or a photoelectric cell, elicit some reaction of the organism or some machinery, and thus convey information." (Ludwig von Bertalanffy, "General System Theory", 1968) 

"The 'flow of information' through human communication channels is enormous. So far no theory exists, to our knowledge, which attributes any sort of unambiguous measure to this 'flow'." (Anatol Rapoport, "Modern Systems Research for the Behavioral Scientist", 1969)

"Probability plays a central role in many fields, from quantum mechanics to information theory, and even older fields use probability now that the presence of "noise" is officially admitted. The newer aspects of many fields start with the admission of uncertainty." (Richard Hamming, "Methods of Mathematics Applied to Calculus, Probability, and Statistics", 1985)

"The field of 'information theory' began by using the old hardware paradigm of transportation of data from point to point." (Marshall McLuhan & Eric McLuhan, Laws of Media: The New Science, 1988)

"Without an understanding of causality there can be no theory of communication. What passes as information theory today is not communication at all, but merely transportation." (Marshall McLuhan & Eric McLuhan, "Laws of Media: The New Science", 1988)

"If quantum communication and quantum computation are to flourish, a new information theory will have to be developed." (Hans Christian von Baeyer, "Information, The New Language of Science", 2003)

"In fact, an information theory that leaves out the issue of noise turns out to have no content." (Hans Christian von Baeyer, "Information, The New Language of Science", 2003)

"In an information economy, entrepreneurs master the science of information in order to overcome the laws of the purely physical sciences. They can succeed because of the surprising power of the laws of information, which are conducive to human creativity. The central concept of information theory is a measure of freedom of choice. The principle of matter, on the other hand, is not liberty but limitation - it has weight and occupies space." (George Gilder, "Knowledge and Power: The Information Theory of Capitalism and How it is Revolutionizing our World", 2013)

"Information theory leads to the quantification of the information content of the source, as denoted by entropy, the characterization of the information-bearing capacity of the communication channel, as related to its noise characteristics, and consequently the establishment of the relationship between the information content of the source and the capacity of the channel. In short, information theory provides a quantitative measure of the information contained in message signals and help determine the capacity of a communication system to transfer this information from source to sink over a noisy channel in a reliable fashion." (Ali Grami, "Information Theory", 2016)

On Symbols (1960-1969)

"By a symbol I do not mean an allegory or a sign, but an image that describes in the best possible way the dimly discerned nature of the spirit. A symbol does not define or explain; it points beyond itself to a meaning that is darkly divined yet still beyond our grasp, and cannot be adequately expressed in the familiar words of our language." (Carl G Jung, "The Structure And Dynamics Of The Psyche", 1960)

"Language, in its origin and essence, is simply a system of signs or symbols that denote real occurrences or their echo in the human soul." (Carl G Jung, "The Structure And Dynamics Of The Psyche", 1960)

"Cybernetics is concerned primarily with the construction of theories and models in science, without making a hard and fast distinction between the physical and the biological sciences. The theories and models occur both in symbols and in hardware, and by 'hardware’ we shall mean a machine or computer built in terms of physical or chemical, or indeed any handleable parts." (Frank H George, "The Brain As A Computer", 1962)

"Science is the reduction of the bewildering diversity of unique events to manageable uniformity within one of a number of symbol systems, and technology is the art of using these symbol systems so as to control and organize unique events. Scientific observation is always a viewing of things through the refracting medium of a symbol system, and technological praxis is always handling of things in ways that some symbol system has dictated. Education in science and technology is essentially education on the symbol level." (Aldous L Huxley, "Essay", Daedalus, 1962)

"For Science in its totality, the ultimate goal is the creation of a monistic system in which - on the symbolic level and in terms of the inferred components of invisibility and intangibly fine structure - the world’s enormous multiplicity is reduced to something like unity, and the endless successions of unique events of a great many different kinds get tidied and simplified into a single rational order. Whether this goal will ever be reached remains to be seen. Meanwhile we have the various sciences, each with its own system coordinating concepts, its own criterion of explanation." (Aldous Huxley, "Literature and Science", 1963)

"It is always extremely difficult to express thoughts. Words and phrases are so many fretters by which our spirit is bound. Words are mere symbols of reality, and the written word is not more than a one-dimensional fl ow across the two-dimensional page of a three-dimensional book." (Charles-Noël Martin, "The Role of Perception in Science", 1963)

"The aim of science is to apprehend this purely intelligible world as a thing in itself, an object which is what it is independently of all thinking, and thus antithetical to the sensible world. [...] The world of thought is the universal, the timeless and spaceless, the absolutely necessary, whereas the world of sense is the contingent, the changing and moving appearance which somehow indicates or symbolizes it." (Robin G Collingwood, "Essays in the Philosophy of Art", 1964)

"This language controls by reducing the linguistic forms and symbols of reflection, abstraction, development, contradiction; by substituting images for concepts. It denies or absorbs the transcendent vocabulary; it does not search for but establishes and imposes truth and falsehood." (Herbert Marcuse, "One-Dimensional Man", 1964)

"Thus a word or an image is symbolic when it implies something more than its obvious and immediate meaning. It has a wider ‘unconscious’ aspect that is never precisely defined or fully explained. […] As the mind explores the symbols it is led to ideas that lie beyond the grasp of reason." (Carl G Jung, "Man and His Symbols", 1964)

"[…] it took men about five thousand years, counting from the beginning of number symbols, to think of a symbol for nothing." (Isaac Asimov, "Of Time and Space and Other Things" , 1965)

"Specific procedures of universe-maintenance become necessary when the symbolic universe has become a problem. As long as this is not the case, the symbolic universe is self-maintaining, that is, self-legitimating by the sheer facticity of its objective existence in the society in question." (Peter L Berger, "The Social Construction of Reality", 1966) 

"There is nothing that can be said by mathematical symbols and relations which cannot also be said by words. The converse, however, is false. Much that can be and is said by words cannot successfully be put into equations, because it is nonsense." (Clifford A Truesdell, "Six Lectures on Modern Natural Philosophy", 1966)

"The symbol is the tool which gives man his power, and it is the same tool whether the symbols are images or words, mathematical signs or mesons." (Jacob Bronowski, "The Reach of Imagination", 1967)

"Symbolic interactionism rests [...] on three simple premises. The first premise is that human beings act toward things on the basis of the meanings that the things have for them. [...] The second premise is that the meaning of such things is derived from, or arises out of, the social interaction that one has with one's fellows. The third premise is that these meanings are handled in, and modified through, an interpretative process used by the person in dealing with the things he encounters." (Herbert Blumer, "Symbolic Interactionism", 1969)

On Symbols (1980-1989)

"[…] mathematics is not just a symbolism, a set of conventions for the use of special, formal vocabularies, but is intimately connected with the structure of rational thought, with reasoning practices. [...] mathematics is not just a language, and of refusing the foundationalist move of trying to reduce mathematics to logic, instead seeing mathematics as providing rational frameworks for science, is to set science against a background of rational structures and rational methods which itself has a built-in dynamics. The rational framework of science is itself historically conditioned, for it changes with developments in mathematics." (Mary Tiles, "Bachelard: Science and Objectivity", 1984)

"Scientific laws give algorithms, or procedures, for determining how systems behave. The computer program is a medium in which the algorithms can be expressed and applied. Physical objects and mathematical structures can be represented as numbers and symbols in a computer, and a program can be written to manipulate them according to the algorithms. When the computer program is executed, it causes the numbers and symbols to be modified in the way specified by the scientific laws. It thereby allows the consequences of the laws to be deduced." (Stephen Wolfram, "Computer Software in Science and Mathematics", 1984)

"A computer is an interpreted automatic formal system - that is to say, a symbol-manipulating machine." (John Haugeland, "Artificial intelligence: The very idea", 1985)

"We who are heirs to three recent centuries of scientific development can hardly imagine a state of mind in which many mathematical objects were regarded as symbols of spiritual truths or episodes in sacred history. Yet, unless we make this effort of imagination, a fraction of the history of mathematics is incomprehensible.” (Philip J Davis & Rueben Hersh, “The Mathematical Experience”, 1985)

"When a graph is constructed, quantitative and categorical information is encoded, chiefly through position, size, symbols, and color. When a person looks at a graph, the information is visually decoded by the person's visual system. A graphical method is successful only if the decoding process is effective. No matter how clever and how technologically impressive the encoding, it is a failure if the decoding process is a failure. Informed decisions about how to encode data can be achieved only through an understanding of the visual decoding process, which is called graphical perception." (William S Cleveland, "The Elements of Graphing Data", 1985)

"Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped onto the other (the computer)." (George Johnson, "Machinery of the Mind: Inside the New Science of Artificial Intelligence", 1986)

"Meaning does not reside in the mathematical symbols. It resides in the cloud of thought enveloping these symbols. It is conveyed in words; these assign meaning to the symbols." (Marvin Chester, "Primer of Quantum Mechanics", 1987)

"[…] the chain of possible combinations of the encounter can be studied as such, as an order which subsists in its rigor, independently of all subjectivity. Through cybernetics, the symbol is embodied in the apparatus - with which it is not to be confused, the apparatus being just its support. And it is embodied in it in a literally trans-subjective way." (Jacques Lacan, 1988)

"Western culture’s world-view appears to be dominated by material objects. […] One of the ways mathematics has gained its power is through the activity of objectivising the abstractions from reality. Through its symbols (letters, numerals, figures) mathematics has taught people how to deal with abstract entities, as if they were objects." (Alan J Bishop, "Mathematics education in its cultural context", Educational Studies in Mathematics 19, 1988)

"People who have a casual interest in mathematics may get the idea that a topologist is a mathematical playboy who spends his time making Möbius bands and other diverting topological models. If they were to open any recent textbook in topology, they would be surprised. They would find page after page of symbols, seldom relieved by a picture or diagram." (Martin Gardner, "Hexaflexagons and Other Mathematical Diversions", 1988)

On Networks (2010-2019)

"We are beginning to see the entire universe as a holographically interlinked network of energy and information, organically whole and self referential at all scales of its existence. We, and all things in the universe, are non-locally connected with each other and with all other things in ways that are unfettered by the hitherto known limitations of space and time." (Ervin László,"Cosmos: A Co-creator's Guide to the Whole-World", 2010)

"The people we get along with, trust, feel simpatico with, are the strongest links in our networks." (Daniel Goleman, "Working With Emotional Intelligence", 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)

"If we create networks with the sole intention of getting something, we won't succeed. We can't pursue the benefits of networks; the benefits ensue from investments in meaningful activities and relationships." (Adam Grant, "Give and Take: A Revolutionary Approach to Success", 2013) 

"Information is recorded in vast interconnecting networks. Each idea or image has hundreds, perhaps thousands, of associations and is connected to numerous other points in the mental network." (Peter Russell, "The Brain Book: Know Your Own Mind and How to Use it", 2013) 

"All living systems are networks of smaller components, and the web of life as a whole is a multilayered structure of living systems nesting within other living systems - networks within networks." (Fritjof Capra, "The Systems View of Life: A Unifying Vision", 2014)

"All the variables we can observe in an ecosystem-population densities, availability of nutrients, weather patterns, and so forth-always fluctuate. This is how ecosystems maintain themselves in a flexible state, ready to adapt to changing conditions. The web of life is a flexible, ever-fluctuating network. The more variables are kept fluctuating, the more dynamic is the system; the greater is its flexibility; and the greater is its ability to adapt to changing conditions." (Fritjof Capra, "The Systems View of Life: A Unifying Vision", 2014)

"Deep ecology does not separate humans - or anything else-from the natural environment. It sees the world not as a collection of isolated objects, but as a network of phenomena that are fundamentally interconnected and interdependent. Deep ecology recognizes the intrinsic value of all living beings and views humans as just one particular strand in the web of life." (Fritjof Capra, "The Systems View of Life: A Unifying Vision", 2014)

"In other words, the web of life consists of networks within networks. At each scale, under closer scrutiny, the nodes of the network reveal themselves as smaller networks. We tend to arange these systems, all nesting within larger systems, in a hierarchical scheme by placing the larger systems above the smaller ones in pyramid fashion. But this is a human projection. In nature there is no 'above' or 'below', and there are no hierarchies. There are only networks nesting within other networks." (Fritjof Capra, "The Systems View of Life: A Unifying Vision", 2014)

"The first and most obvious property of any network is its nonlinearity – it goes in all directions. Thus the relationships in a network pattern are nonlinear relationships. In particular, an influence, or message, may travel along a cyclical path, which may become a feedback loop. In living networks, the concept of feedback is intimately connected with the network pattern." (Fritjof Capra, "The Systems View of Life: A Unifying Vision", 2014)

"Whenever we encounter living systems – organisms, parts of organisms, or communities of organisms – we can observe that their components are arranged in network fashion. Whenever we look at life, we look at networks." (Fritjof Capra, "The Systems View of Life: A Unifying Vision", 2014)

"A network (or graph) consists of a set of nodes (or vertices, actors) and a set of edges (or links, ties) that connect those nodes. [...] The size of a network is characterized by the numbers of nodes and edges in it." (Hiroki Sayama, "Introduction to the Modeling and Analysis of Complex Systems", 2015)

"A worldview consists of observations of the individual and other people with respect to the self, time and space, the natural and the supernatural and the sacred and profane. […] Beliefs about the world do not reside in the human mind in chaotic disorder; rather they form a latent system. A worldview cannot, however, be viewed as a well-organised network of cognitive models or a static collection of values; instead it should be regarded as the product of a process shaped by historical, cultural and social perspectives and contexts." (Helena Helve, "A longitudinal perspective on worldviews, values and identities", 2016)

"Although cascading failures may appear random and unpredictable, they follow reproducible laws that can be quantified and even predicted using the tools of network science. First, to avoid damaging cascades, we must understand the structure of the network on which the cascade propagates. Second, we must be able to model the dynamical processes taking place on these networks, like the flow of electricity. Finally, we need to uncover how the interplay between the network structure and dynamics affects the robustness of the whole system." (Albert-László Barabási, "Network Science", 2016)

"The exploding interest in network science during the first decade of the 21st century is rooted in the discovery that despite the obvious diversity of complex systems, the structure and the evolution of the networks behind each system is driven by a common set of fundamental laws and principles. Therefore, notwithstanding the amazing differences in form, size, nature, age, and scope of real networks, most networks are driven by common organizing principles. Once we disregard the nature of the components and the precise nature of the interactions between them, the obtained networks are more similar than different from each other." (Albert-László Barabási, "Network Science", 2016)

"Network theory confirms the view that information can take on 'a life of its own'. In the yeast network my colleagues found that 40 per cent of node pairs that are correlated via information transfer are not in fact physically connected; there is no direct chemical interaction. Conversely, about 35 per cent of node pairs transfer no information between them even though they are causally connected via a 'chemical wire' (edge). Patterns of information traversing the system may appear to be flowing down the 'wires' (along the edges of the graph) even when they are not. For some reason, 'correlation without causation' seems to be amplified in the biological case relative to random networks." (Paul Davies, "The Demon in the Machine: How Hidden Webs of Information Are Solving the Mystery of Life", 2019)

"The concept of integrated information is clearest when applied to networks. Imagine a black box with input and output terminals. Inside are some electronics, such as a network with logic elements (AND, OR, and so on) wired together. Viewed from the outside, it will usually not be possible to deduce the circuit layout simply by examining the cause–effect relationship between inputs and outputs, because functionally equivalent black boxes can be built from very different circuits. But if the box is opened, it’s a different story. Suppose you use a pair of cutters to sever some wires in the network. Now rerun the system with all manner of inputs. If a few snips dramatically alter the outputs, the circuit can be described as highly integrated, whereas in a circuit with low integration the effect of some snips may make no difference at all." (Paul Davies, "The Demon in the Machine: How Hidden Webs of Information Are Solving the Mystery of Life", 2019)

"[...] the Game of Life, in which a few simple rules executed repeatedly can generate a surprising degree of complexity. Recall that the game treats squares, or pixels, as simply on or off (filled or blank) and the update rules are given in terms of the state of the nearest neighbours. The theory of networks is closely analogous. An electrical network, for example, consists of a collection of switches with wires connecting them. Switches can be on or off, and simple rules determine whether a given switch is flipped, according to the signals coming down the wires from the neighbouring switches. The whole network, which is easy to model on a computer, can be put in a specific starting state and then updated step by step, just like a cellular automaton. The ensuing patterns of activity depend both on the wiring diagram (the topology of the network) and the starting state. The theory of networks can be developed quite generally as a mathematical exercise: the switches are called ‘nodes’ and the wires are called ‘edges’. From very simple network rules, rich and complex activity can follow." (Paul Davies, "The Demon in the Machine: How Hidden Webs of Information Are Solving the Mystery of Life", 2019)

"[...] the same network may exhibit fundamentally different patterns of information flow under different dynamics: epidemic spread, ecological interactions, or genetic regulation." (Uzi Harush & Baruch Barzel, "Dynamic patterns of information flow in complex networks", Nature Communications, 2017)

"And that’s what good networkers do. No matter the field, discipline, or industry, if we want to succeed, we must master the networks. Because as the First Law of Success reminds us, the harder it is to measure performance, the less performance matters." (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)

Gordon Pask - Collected Quotes

"By definition, a pair of inherently unmeasurable, non-stationary systems, are coupled to produce an inherently measurable stationary system." (Gordon Pask, "An Approach to Cybernetics", 1961) 

"Cybernetics offers a scientific approach to the cussedness of organisms, suggests how their behaviours can be catalysed and the mystique and rule of thumb banished." (Gordon Pask, "An Approach to Cybernetics", 1961)

"Cybernetics is the science or the art of manipulating defensible metaphors; showing how they may be constructed and what can be inferred as a result of their existence." (Gordon Pask, "The Cybernetics of Human Performance and Learning", 1966) 

"Development of an organism from a single germ cell into a multicellular entity is a self-organizing system from any point of view and I wish to contend that this self-organizing system is a subsystem of the self-organizing system called 'evolution'." (Gordon Pask, "An Approach to Cybernetics", 1961) 

"Any theory starts off with an observer or experimenter. He has in mind a collection of abstract models with predictive capabilities. Using various criteria of relevance, he selects one of them. In order to actually make predictions, this model must be interpreted and identified with a real assembly to form a theory. The interpretation may be prescriptive or predictive, as when the model is used like a blueprint for designing a machine and predicting its states. On the other hand, it may be descriptive and predictive as it is when the model is used to explain and predict the behaviour of a given organism." (Gordon Pask, "The meaning of cybernetics in the behavioural sciences", 1969)

"There are two subcategories of holist called irredundant holists and redundant holists. Students of both types image an entire system of facts or principles. Though an irredundant holist's image is rightly interconnected, it contains only relevant and essential constitents. In contrast, redundant holists entertain images that contain logically irrelevant or overspecific material, commonly derived from data used to 'enrich' the curriculum, and these students embed the salient facts and principles in a network of redundant items. Though logically irrelevant, the items in question are of great psychological importance to a 'redundant holist', since he uses them to access, retain and manipulate whatever he was originally required to learn." (Gordon Pask, "Learning Strategies and Individual Competence", 1972)

"A learning strategy is comparable in kind with a performance strategy. Each sort of strategy entails decomposing goals into subgoals and applying mental subroutines to achieve the subgoals concerned. The necessary difference between learning strategies and performance is in the domain upon which they operate. Whereas the performance strategy solves problems posed by states of the (usually symbolic) environment, the learning strategy solves the problems posed by deficiencies in the current repertoire of relevant performance strategies; the solutions produced by a learning strategy are performance strategies."(Gordon Pask, "Conversation, Cognition and Learning", 1975)

"If cognitive processes can be realized in a general machine then it is possible to execute mental operations in artifacts that are not necessarily subject to the embarrassing spatio-temporal limitations and structural frailties of a biological processor." (Gordon Pask, "Conversation, Cognition and Learning", 1975)

"Regarding stability, the state trajectories of a system tend to equilibrium. In the simplest case they converge to one point (or different points from different initial states), more commonly to one (or several, according to initial state) fixed point or limit cycle(s) or even torus(es) of characteristic equilibrial behaviour. All this is, in a rigorous sense, contingent upon describing a potential, as a special summation of the multitude of forces acting upon the state in question, and finding the fixed points, cycles, etc., to be minima of the potential function. It is often more convenient to use the equivalent jargon of 'attractors' so that the state of a system is 'attracted' to an equilibrial behaviour. In any case, once in equilibrial conditions, the system returns to its limit, equilibrial behaviour after small, arbitrary, and random perturbations." (Gordon Pask, "Different Kinds of Cybernetics", 1992)

"Systems, acting dynamically, produce (and incidentally, reproduce) their own boundaries, as structures which are complementary (necessarily so) to their motion and dynamics. They are liable, for all that, to instabilities chaos, as commonly interpreted of chaotic form, where nowadays, is remote from the random. Chaos is a peculiar situation in which the trajectories of a system, taken in the traditional sense, fail to converge as they approach their limit cycles or 'attractors' or 'equilibria'. Instead, they diverge, due to an increase, of indefinite magnitude, in amplification or gain." (Gordon Pask, "Different Kinds of Cybernetics", 1992)

On Cybernetics (2000-2009)

"An opportunity for cybernetics to change the course of the philosophy of mind was missed when intentionality was misinterpreted as 'the providing of coded knowledge'." (Igor Aleksander, New Scientist Vol. 169, 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) 

“The shocking thing is that there is truth in every one of these notions, and the reason is because cybernetics is an interdisciplinary subject. It must be complicated." (Stafford Beer, "What is cybernetics?", Kybernetes, 2002)

"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)

"Cybernetics is the study of systems and processes that interact with themselves and produce themselves from themselves." (Louis Kauffman, 2007)

"Systematic usage of the methods of modern control theory to study physical systems is a key feature of a new research area in physics that may be called cybernetical physics. The subject of cybernetical physics is focused on studying physical systems by means of feedback interactions with the environment. Its methodology heavily relies on the design methods developed in cybernetics. However, the approach of cybernetical physics differs from the conventional use of feedback in control applications (e.g., robotics, mechatronics) aimed mainly at driving a system to a prespecified position or a given trajectory." (Alexander L Fradkov, "Cybernetical Physics: From Control of Chaos to Quantum Control", 2007)

"The methodology of feedback design is borrowed from cybernetics (control theory). It is based upon methods of controlled system model’s building, methods of system states and parameters estimation (identification), and methods of feedback synthesis. The models of controlled system used in cybernetics differ from conventional models of physics and mechanics in that they have explicitly specified inputs and outputs. Unlike conventional physics results, often formulated as conservation laws, the results of cybernetical physics are formulated in the form of transformation laws, establishing the possibilities and limits of changing properties of a physical system by means of control." (Alexander L Fradkov, "Cybernetical Physics: From Control of Chaos to Quantum Control", 2007)

"For me, as I later came to say, cybernetics is the art of creating equilibrium in a world of possibilities and constraints. This is not just a romantic description, it portrays the new way of thinking quite accurately. Cybernetics differs from the traditional scientific procedure, because it does not try to explain phenomena by searching for their causes, but rather by specifying the constraints that determine the direction of their development." (Ernst von Glasersfeld, "The Cybernetics of Snow Drifts 1948", 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)

On Self-Organization IV

"Every system of whatever size must maintain its own structure and must deal with a dynamic environment, i.e., the system must strike a proper balance between stability and change. The cybernetic mechanisms for stability (i.e., homeostasis, negative feedback, autopoiesis, equifinality) and change (i.e., positive feedback, algedonodes, self-organization) are found in all viable systems." (Barry Clemson, "Cybernetics: A New Management Tool", 1984)

"Autopoietic systems, then, are not only self-organizing systems, they not only produce and eventually change their own structures; their self-reference applies to the production of other components as well. This is the decisive conceptual innovation. […] Thus, everything that is used as a unit by the system is produced as a unit by the system itself. This applies to elements, processes, boundaries, and other structures and, last but not least, to the unity of the system itself." (Niklas Luhmann, "The Autopoiesis of Social Systems", 1990)

"The cybernetics phase of cognitive science produced an amazing array of concrete results, in addition to its long-term (often underground) influence: the use of mathematical logic to understand the operation of the nervous system; the invention of information processing machines (as digital computers), thus laying the basis for artificial intelligence; the establishment of the metadiscipline of system theory, which has had an imprint in many branches of science, such as engineering (systems analysis, control theory), biology (regulatory physiology, ecology), social sciences (family therapy, structural anthropology, management, urban studies), and economics (game theory); information theory as a statistical theory of signal and communication channels; the first examples of self-organizing systems. This list is impressive: we tend to consider many of these notions and tools an integrative part of our life […]" (Francisco Varela, "The Embodied Mind", 1991)

"Through self-organization, the behavior of the group emerges from the collective interactions of all the individuals. In fact, a major recurring theme in swarm intelligence (and of complexity science in general) is that even if individuals follow simple rules, the resulting group behavior can be surprisingly complex - and remarkably effective. And, to a large extent, flexibility and robustness result from self-organization." (Eric Bonabeau & Christopher Meyer, "Swarm Intelligence: A Whole New Way to Think About Business", Harvard Business Review, 2001)

"[…] swarm intelligence is becoming a valuable tool for optimizing the operations of various businesses. Whether similar gains will be made in helping companies better organize themselves and develop more effective strategies remains to be seen. At the very least, though, the field provides a fresh new framework for solving such problems, and it questions the wisdom of certain assumptions regarding the need for employee supervision through command-and-control management. In the future, some companies could build their entire businesses from the ground up using the principles of swarm intelligence, integrating the approach throughout their operations, organization, and strategy. The result: the ultimate self-organizing enterprise that could adapt quickly - and instinctively - to fast-changing markets." (Eric Bonabeau & Christopher Meyer, "Swarm Intelligence: A Whole New Way to Think About Business", Harvard Business Review, 2001)

"A system described as self-organizing is one in which elements interact in order to achieve dynamically a global function or behavior." (Carlos Gershenson, "A general methodology for designing self-organizing systems", 2006)

"In engineering, a self-organizing system would be one in which elements are designed to dynamically and autonomously solve a problem or perform a function at the system level. In other words, the engineer will not build a system to perform a function explicitly, but elements will be engineered in such a way that their behaviour and interactions will lead to the system function. Thus, the elements need to divide, but also to integrate, the problem." (Carlos Gershenson, "Design and Control of Self-organizing Systems", 2007)

"The second law of thermodynamics states that in an isolated system, entropy can only increase, not decrease. Such systems evolve to their state of maximum entropy, or thermodynamic equilibrium. Therefore, physical self-organizing systems cannot be isolated: they require a constant input of matter or energy with low entropy, getting rid of the internally generated entropy through the output of heat ('dissipation'). This allows them to produce ‘dissipative structures’ which maintain far from thermodynamic equilibrium. Life is a clear example of order far from thermodynamic equilibrium." (Carlos Gershenson, "Design and Control of Self-organizing Systems", 2007)

"Most systems in nature are inherently nonlinear and can only be described by nonlinear equations, which are difficult to solve in a closed form. Non-linear systems give rise to interesting phenomena such as chaos, complexity, emergence and self-organization. One of the characteristics of non-linear systems is that a small change in the initial conditions can give rise to complex and significant changes throughout the system. This property of a non-linear system such as the weather is known as the butterfly effect where it is purported that a butterfly flapping its wings in Japan can give rise to a tornado in Kansas. This unpredictable behaviour of nonlinear dynamical systems, i.e. its extreme sensitivity to initial conditions, seems to be random and is therefore referred to as chaos. This chaotic and seemingly random behaviour occurs for non-linear deterministic system in which effects can be linked to causes but cannot be predicted ahead of time." (Robert K Logan, "The Poetry of Physics and The Physics of Poetry", 2010)

"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)

C West Churchman - Collected Quotes

"The individuation process, as the way of development and maturation of the psyche, does not follow a straight line, nor does it always lead onwards and upwards. The course it follows is rather 'stadial', consisting of progress and regress, flux and stagnation in alternating sequence. Only when we glance back over a long stretch of the way can we notice the development. If we wish to mark out the way somehow or other, it can equally well be considered a' spiral', the same problems and motifs occurring again and again on different levels." (C West Churchman, "Theory of Experimental Inference", 1948) 

"The concepts and methods of cybernetics are by no means restricted to the problems of servo-mechanisms, or even neural physiology, though the impetus came from these areas. […] Cybernetics analyzes all purposive behavior and provides an exact notion of communication and the transmital of information." (C West Churchman & Russel L Ackoff, "Purposive Behavior and Cybernetics", Social Forces Vol. 29 (1), 1950)

"Scientists whose work has no clear, practical implications would want to make their decisions considering such things as: the relative worth of (1) more observations, (2) greater scope of his conceptual model, (3) simplicity, (4) precision of language, (5) accuracy of the probability assignment." (C West Churchman, "Costs, Utilities, and Values", 1956)

"We have overwhelming evidence that available information plus analysis does not lead to knowledge. The management science team can properly analyse a situation and present recommendations to the manager, but no change occurs. The situation is so familiar to those of us who try to practice management science that I hardly need to describe the cases." (C West Churchman, "Managerial acceptance of scientific recommendations", California Management Review Vol 7, 1964) 

"A systems approach begins when first you see the world through the eyes of another." (C West Churchman, "The Systems Approach", 1968)

"It is sheer nonsense to expect that any human being has yet been able to attain such insight into the problems of society that he can really identify the central problems and determine how they should be solved. The systems in which we live are far too complicated as yet for our intellectual powers and technology to understand." (C West Churchman, 1968) 

"The systems approach goes on to discovering that every world-view is terribly restricted." (C West Churchman, 1970)

"To know that we are measuring real change we need to have a strong theoretical base." (C West Churchman, 1970)

"A system may actually exist as a natural aggregation of component parts found in Nature, or it may be a man-contrived aggregation – a way of looking at a problem which results from a deliberate decision to assume that a set of elements are related and constitute such a thing called 'a system'." (C West Churchman et al, "Thinking for Decisions Deduction Quantitative Methods", 1975)

"The theory of the nature of mathematics is extremely reactionary. We do not subscribe to the fairly recent notion that mathematics is an abstract language based, say, on set theory. In many ways, it is unfortunate that philosophers and mathematicians like Russell and Hilbert were able to tell such a convincing story about the meaning-free formalism of mathematics. [...] Mathematics is a way of preparing for decisions through thinking. Sets and classes provide one way to subdivide a problem for decision preparation; a set derives its meaning from decision making, and not vice versa." (C West Churchman et al, "Thinking for Decisions Deduction Quantitative Methods", 1975)

"Holism traditionally says that a collection of beings may have a collective property that cannot be inferred from the properties of its members." (C West Churchman, "The Systems Approach and Its Enemies" , 1979)

"The measure of our intellectual capacity is the capacity to feel less and less satisfied with our answers to better and better problems." (C West Churchman) 

Mental Models LIII (Conceptual Models II)

"But metaphor is an indispensable tool of thought and expression - a characteristic of all human communication, even of that of the scientist. The conceptual models of cybernetics and the energy theories of psycho-analysis are, after all, only labeled metaphors." (Gregory Bateson, "Steps to an Ecology of Mind", 1972)

"[…] conceptual models, even when incorrect, are useful to the extent that criticism of the model may point to new theoretical developments."  (Gregory Bateson, "Steps to an Ecology of Mind", 1972)

"As the least conscious layer of the user experience, the conceptual model has the paradoxical quality of also having the most impact on usability. If an appropriate conceptual model is faithfully represented throughout the interface, after users recognize and internalize the model, they will have a fundamental understanding of what the application does and how to operate it." (Bob Baxley, "Making the Web Work: Designing Effective Web Applications", 2002) 

"A conceptual model of an interactive application is, in summary: the structure of the application - the objects and their operations, attributes, and relation-ships; an idealized view of the how the application works – the model designers hope users will internalize; the mechanism by which users accomplish the tasks the application is intended to support." (Jeff Johnson & Austin Henderson, "Conceptual Models", 2011)

"Conceptual models are best thought of as design-tools - a way for designers to straighten out and simplify the design and match it to the users’ task-domain, thereby making it clearer to users how they should think about the application. The designers’ responsibility is to devise a conceptual model that seems natural to users based on the users’ familiarity with the task domain. If designers do their job well, the conceptual model will be the basis for users’ mental models of the application." (Jeff Johnson & Austin Henderson, "Conceptual Models", 2011)

"The conceptual model is not the users’ mental model of the application. […] users of an application form mental models of it to allow them to predict its behavior. A mental model is the user’s high-level understanding of how the application works; it allows the user to predict what the application will do in response to various user-actions. Ideally, a user’s mental model of an application should be similar to the designers’ conceptual model, but in practice the two models may differ significantly. Even if a user’s mental model is the same as the designer’s conceptual model, they are distinct models." (Jeff Johnson & Austin Henderson, "Conceptual Models", 2011)

"Briefly, a conceptual model is the configuration of conceptual elements and the navigation between them. As such, a conceptual model is the foundation of the user interface of any interactive system." (Avi Parush, "Conceptual Design for Interactive Systems", 2015)

"A conceptual model is a framework that is initially used in research to outline the possible courses of action or to present an idea or thought. When a conceptual model is developed in a logical manner, it will provide a rigor to the research process." (N Elangovan & R Rajendran, "Conceptual Model: A Framework for Institutionalizing the Vigor in Business Research", 2015) 

"Once we understand our user's mental model, we can capture it in a conceptual model. The conceptual model is a representation of the mental model using elements, relationships, and conditions. Our design and final system will be the tangible result of this conceptual model." (Pau Giner & Pablo Perea, "UX Design for Mobile, 2017) 

"A model or conceptual model is a schematic or representation that describes how something works. We create and adapt models all the time without realizing it. Over time, as you gain more information about a problem domain, your model will improve to better match reality." (James Padolsey, "Clean Code in JavaScript", 2020)

Collective Intelligence I

"We must therefore establish a form of decision-making in which voters need only ever pronounce on simple propositions, expressing their opinions only with a yes or a no. […] Clearly, if anyone’s vote was self-contradictory (intransitive), it would have to be discounted, and we should therefore establish a form of voting which makes such absurdities impossible." (Nicolas de Condorcet, "On the form of decisions made by plurality vote", 1788)

"Collective wisdom, alas, is no adequate substitute for the intelligence of individuals. Individuals who opposed received opinions have been the source of all progress, both moral and intellectual. They have been unpopular, as was natural." (Bertrand Russell, "Why I Am Not a Christian", 1927)

"The collective intelligence of any group of people who are thinking as a 'herd' rather than individually is no higher than the intelligence of the stupidest members. (Mary Day Winn, Adam's Rib, 1931)

"Learning is a property of all living organisms. […] Since organized groups can be looked upon as living entities, they can be expected to exhibit learning […]" (Winfred B. Hirschmann, "Profit from the Learning Curve", Harvard Business Review, 1964)

"A cardinal principle in systems theory is that all parties that have a stake in a system should be represented in its management." (Malcolm S Knowles, "The Adult Learner", 1973)

"Collective intelligence emerges when a group of people work together effectively. Collective intelligence can be additive (each adds his or her part which together form the whole) or it can be synergetic, where the whole is greater than the sum of its parts." (Trudy and Peter Johnson-Lenz, "Groupware: Orchestrating the Emergence of Collective Intelligence", cca. 1980)

"Cybernetic information theory suggests the possibility of assuming that intelligence is a feature of any feedback system that manifests a capacity for learning." (Paul Hawken et al, "Seven Tomorrows", 1982)

"The concept of organizational learning refers to the capacity of organizational complexes to develop experiential knowledge, instincts, and 'feel' or intuition which are greater than the combined knowledge, skills and instincts of the individuals involved." (Don E. Kash, "Perpetual Innovation", 1989)

"We haven't worked on ways to develop a higher social intelligence […] We need this higher intelligence to operate socially or we're not going to survive. […] If we don't manage things socially, individual high intelligence is not going to make much difference. [...] Ordinary thought in society is incoherent - it is going in all sorts of directions, with thoughts conflicting and canceling each other out. But if people were to think together in a coherent way, it would have tremendous power." (David Bohm, "New Age Journal", 1989)

Maxwell Maltz - Collected Quotes

"A human being always acts and feels and performs in accordance with what he imagines to be true about himself and his environment." (Maxwell Maltz, "Psycho-Cybernetics", 1960)

"An idea accepted as true from any source can be every bit as powerful as hypnosis." (Maxwell Maltz, "Psycho-Cybernetics", 1960)

"For imagination sets the goal picture which our automatic mechanism works on. We act, or fail to act, not because of will, as is so commonly believed, but because of imagination." (Maxwell Maltz, "Psycho-Cybernetics", 1960)

"It is no exaggeration to say that every human being is hypnotized to some extent either by ideas he has uncritically accepted from others or ideas he has repeated to himself or convinced himself are true. These negative ideas have exactly the same effect upon our behavior as the negative ideas implanted into the mind of a hypnotized subject by a professional hypnotist." (Maxwell Maltz, "Psycho-Cybernetics", 1960)

"Mental pictures offer us an opportunity to practice new traits and attitudes, which otherwise we could not do. This is possible because again - your nervous system cannot tell the difference between an actual experience and one that is vividly imagined." (Maxwell Maltz, "Psycho-Cybernetics", 1960)

"The ‘self-image’ is the key to human personality and human behavior. Change the self image and you change the personality and the behavior." (Maxwell Maltz, "Psycho-Cybernetics", 1960)

"Your automatic creative mechanism is teleological. That is, it operates in terms of goals and end results. Once you give it a definite goal to achieve, you can depend upon its automatic guidance system to take you to that goal much better than ‘you’ ever could by conscious tthought. 'You’ supply the goal by thinking in terms of end results. Your automatic mechanism then supplies the means whereby." (Maxwell Maltz, "Psycho-Cybernetics", 1960)

Valentin F Turchin - Collected Quotes

"Cybernetics is based above all on the concept of the system, a certain material object which consists of other objects which are called subsystems of the given system. The subsystem of a certain system may, in its turn, be viewed as a system consisting of other subsystems. To be precise, therefore, the meaning of the concept we have introduced does not lie in the term ‘system’ by itself, that is, not in ascribing the property of ‘being a system’ to a certain object (this is quite meaningless, for any object may be considered a system), but rather in the connection between the terms ‘system’ and ‘subsystem’, which reflects definite relationship among objects." (Valentin F Turchin, "The Phenomenon of Science: A cybernetic approach to human evolution", 1977)

"Cybernetics studies the organization of systems in space and time, that is, it studies how subsystems are connected into a system and how change in the state of some subsystems influences the state of other subsystems." (Valentin F Turchin, "The Phenomenon of Science: A cybernetic approach to human evolution", 1977)

"In the process of the evolution of life, as far as we know, the total mass of living matter has always been and is now increasing and growing more complex in its organization. To increase the complexity of the organization of biological forms, nature operates by trial and error. Existing forms are reproduced in many copies, but these are not identical to the original. Instead they differ from it by the presence of small random variations."  (Valentin F Turchin, "The Phenomenon of Science: A cybernetic approach to human evolution", 1977)

"Principles so general that they are applicable both to the evolution of science and to biological evolution require equally general concepts for their expression. Such concepts are offered by cybernetics, the science of relationships, control, and organization in all types of objects." (Valentin F Turchin, "The Phenomenon of Science: A cybernetic approach to human evolution", 1977)

"The branch of modern science called cybernetics gives us concepts that describe the evolutionary process at both the level of intracellular structures and the level of social phenomena. The fundamental unity of the evolutionary process at all levels of organization is transformed from a philosophical view to a scientifically substantiated fact." (Valentin F Turchin, "The Phenomenon of Science: A cybernetic approach to human evolution", 1977)

"[…] the cybernetic approach brings us to another point of view according to which the analogy between society and the organism has a profound meaning, testifying to the existence of extraordinarily general laws of evolution that exist at all levels of the organization of matter and pointing out to us the direction of society's development." (Valentin F Turchin, "The Phenomenon of Science: A cybernetic approach to human evolution", 1977)

"To master a concept means to be able to recognize it, that is, to be able to determine whether or not any given situation belongs to the set that characterizes this concept." (Valentin F Turchin, "The Phenomenon of Science: A cybernetic approach to human evolution", 1977)

On Cybernetics (1970-1979)

"Because the subject matter of cybernetics is the propositional or informational aspect of the events and objects in the natural world, this science is forced to procedures rather different from those of the other sciences. The differentiation, for example, between map and territory, which the semanticists insist that scientists shall respect in their writings must, in cybernetics, be watched for in the very phenomena about which the scientist writes. Expectably, communicating organisms and badly programmed computers will mistake map for territory; and the language of the scientist must be able to cope with such anomalies." (Gregory Bateson, "Steps to an Ecology of Mind", 1972) 

"But metaphor is an indispensable tool of thought and expression - a characteristic of all human communication, even of that of the scientist. The conceptual models of cybernetics and the energy theories of psycho-analysis are, after all, only labeled metaphors." (Gregory Bateson, "Steps to an Ecology of Mind", 1972) 

"I think that cybernetics is the biggest bite out of the fruit of the Tree of Knowledge that mankind has taken in the last 2000 years. But most of such bites out of the apple have proved to be rather indigestible - usually for cybernetic reasons. Cybernetics has integrity within itself, to help us to not be seduced by it into more lunacy, but we cannot trust it to keep us from sin. […] there are other dangers latent in cybernetics and many of these are still unidentified. […] that there is also latent in cybernetics the means of achieving a new and perhaps more human outlook, a means of changing our philosophy of control and a means of seeing our own follies in wider perspective." (Gregory Bateson, "Steps to an Ecology of Mind", 1972) 

"It follows from this that man's most urgent and pre-emptive need is maximally to utilize cybernetic science and computer technology within a general systems framework, to build a meta-systemic reality which is now only dimly envisaged. Intelligent and purposeful application of rapidly developing telecommunications and teleprocessing technology should make possible a degree of worldwide value consensus heretofore unrealizable." (Richard F Ericson, "Visions of Cybernetic Organizations", 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)

"This parallel, between cybernetic explanation and the tactics of logical or mathematical proof, is of more than trivial interest. Outside of cybernetics, we look for explanation, but not for anything which would simulate logical proof. This simulation of proof is something new. We can say, however, with hindsight wisdom, that explanation by simulation of logical or mathematical proof was expectable. After all, the subject matter of cybernetics is not events and objects but the information 'carried' by events and objects. We consider the objects or events only as proposing facts, propositions, messages, percepts, and the like. The subject matter being propositional, it is expectable that explanation would simulate the logical." (Gregory Bateson, "Steps to an Ecology of Mind", 1972) 

"The main object of cybernetics is to supply adaptive, hierarchical models, involving feedback and the like, to all aspects of our environment. Often such modelling implies simulation of a system where the simulation should achieve the object of copying both the method of achievement and the end result. Synthesis, as opposed to simulation, is concerned with achieving only the end result and is less concerned (or completely unconcerned) with the method by which the end result is achieved. In the case of behaviour, psychology is concerned with simulation, while cybernetics, although also interested in simulation, is primarily concerned with synthesis." (Frank H George, "Soviet Cybernetics, the militairy and Professor Lerner", New Scientist, 1973)

"Cybernetics studies the organization of systems in space and time, that is, it studies how subsystems are connected into a system and how change in the state of some subsystems influences the state of other subsystems. The primary emphasis, of course, is on organization in time which, when it is purposeful, is called control. Causal relations between states of a system and the characteristics of its behavior in time which follow from this are often called the dynamics of the system [...]." (Valentin F Turchin,"The Phenomenon of Science: a cybernetic approach to human evolution", 1977)

"Principles so general that they are applicable both to the evolution of science and to biological evolution require equally general concepts for their expression. Such concepts are offered by cybernetics, the science of relationships, control, and organization in all types of objects." (Valentin F Turchin, "The Phenomenon of Science: a cybernetic approach to human evolution", 1977)

"The branch of modern science called cybernetics gives us concepts that describe the evolutionary process at both the level of intracellular structures and the level of social phenomena. The fundamental unity of the evolutionary process at all levels of organization is transformed from a philosophical view to a scientifically substantiated fact." (Valentin F Turchin, "The Phenomenon of Science: A cybernetic approach to human evolution", 1977)

"Cybernetics is a homogenous and coherent scientific complex, a science resulting from the blending of at least two sciences - psychology and technology; it is a general and integrative science, a crossroads of sciences, involving both animal and car psychology. It is not just a discipline, circumscribed in a narrow and strictly defined field, but a complex of disciplines born of psychology and centered on it, branched out as branches of a tree in its stem. It is a stepwise synthesis, a suite of multiple, often reciprocal, modeling; syntheses and modeling in which, as a priority, and as a great importance, the modeling of psychology on the technique and then the modeling of the technique on psychology. Cybernetics is an intellectual symphony, a symphony of ideas and sciences." (Stefan Odobleja, "Psihologia consonantista și cibernetică" ["Consonatist and Cybernetic Psychology"], 1978)