Cybernetics ...
  "the science and art of understanding"... - Humberto Maturana
  "interfaces hard competence with the hard problems of the soft sciences" - Heinz von Foerster
The Subject of Cybernetics

on the shoulders of giants

History of
Noted Contributors
to Cybernetics


    The ASC Glossary was generated quite some time ago. In the 1990's, the American Society for Cybernetics agreed to have its Glossary (along with Klaus Krippendorff's Dictionary of Cybernetics and other similar documents) merged into the Web Dictionary of Cybernetics and Systems maintained at the Principia Cybernetica Web.

This presentation of the original ASC Glossary is meant to augment the lexical resources on cybernetics and systems theory already available online.


ADAPTATION   a form of behavior is adaptive if it maintains the essential variables within physiological limits. For example, the amount of carbon dioxide in the blood is important in its effect on the blood's alkalinity. If the amount rises, the rate and depth of respiration are increased, and carbon dioxide is exhaled at an increased rate. If the amount falls, the reaction is reversed. By this means the alkalinity of the blood is kept within limits.

The retina works best at a certain intensity of illumination. In bright light the nervous system contracts the pupil, and in dim relaxes it. Thus the amount of light entering the eye is maintained within limits.

When dry food is chewed, a copious supply of saliva is poured into the mouth. Saliva lubricates the food and converts it from a harsh and abrasive texture to one which can be chewed without injury. The secretion therefore keeps the frictional stresses below the destructive level.

Many more examples could be given, but all can be included within the same formula. Some external disturbance tends to drive an essential variable outside its normal limits; but the commencing change itself activates a mechanism that opposes the external disturbance. By this mechanism the essential variable is maintained within limits much narrower than would occur if the external disturbance were unopposed. The narrowing is the objective manifestation of the mechanism's adaptation.

Just the same criterion for adaptation may be used in judging the behavior of the free-living animal in its learned reactions. Take the type-problem of the kitten and the fire. When the kitten first approaches an open fire, it may paw at the fire as if at a mouse, or it may crouch down and start to 'stalk' the fire, or it may attempt to sniff at the fire, or it may walk unconcernedly on to it. Every one of these actions is liable to lead to the animal's being burned. Equally the kitten, if it is cold, may sit far from the fire and thus stay cold. The kitten's behavior cannot be called adapted, for the temperature of its skin is not kept within normal limits. The animal, in other words, is not acting homeostatically for skin temperature. Contrast this behavior with that of the experienced cat: on a cold day it approaches the fire to a distance adjusted so that the skin temperature is neither too hot nor too cold. If the fire burns fiercer, the cat will move away until the skin is again warmed to a moderate degree. If the fire burns low the cat will move nearer. If a red-hot coal drops from the fire the cat takes such action as will keep the skin temperature within normal limits. Without making any inquiry at this stage into what has happened to the kitten's brain, we can at least say that whereas at first the kitten's behavior was not homeostatic for skin temperature, it has now become so. Such behavior is 'adapted': it preserves the life of the animal by keeping the essential variables within limits. (Ashby, 1960, pp. 58, 60-62)

ADIABATIC   occurring without loss or gain of heat. (Webster's)

  A fortiori analysis is a method of treating uncertainty that stacks the cards against one ALTERNATIVE (often the one intuitively preferred) by resolving questions of uncertainty in favor of another alternative. If the initially preferred alternative is still preferable, one has a stronger case in its favor. See also: SENSITIVITY ANALYSIS, CONTINGENCY ANALYSIS. (IIASA)

  a term used by Stafford Beer to describe the feedback an organism, organization or machine receives from the environment. The algedonic loop is the large feedback loop that goes outside the organism and, through reward or punishment, indicates the environment's response to the organism's behavior.

  1. A rule or procedure for solving a recurrent mathematical problem.
  2. A complete, unambiguous procedure for solving a specified problem in a finite number of steps. (Richard Dorf)
  3. Deterministic ALGORITHM: Given the same input information, will always produce the same output information, when applied correctly. (John Warfield)
  4. Stochastic ALGORITHM: Given the same information, will not necessarily produce the same output information, even though applied correctly. (John Warfield)
  5. Any mechanical or recursive computational procedure (Dictionary).

ALLOPOIESIS   the process whereby an organization produces something other than the organization itself. An assembly line is an example of an allopoietic system. See AUTOPOIESIS. (Francisco Varela)

  Machines that have as a product of their functioning something different from themselves, as in a car. (Maturana and Varela, 1979)

ALTERNATIVE   One of the mutually exclusive COURSES OF ACTION that are considered as means of attaining the OBJECTIVES. Typically, the alternatives differ in their nature or character, not only in quantitative details. By mutually exclusive we mean that the alternatives are competitive in the sense that if A is selected, B cannot be chosen. A course of action that combines features selected from both A and B would be a new alternative. (The synonym "option" is often used in association with the DECISION MAKER, as in "the decision maker's options were."). (IIASA)

  1. correspondence in some respects, especially in function or position, between things otherwise dissimilar.
  2. a form of logical inference, or an instance of it, based on the assumption that if two things are known to be alike in some respects, then they must be alike in other respects.

ANTICOMMUNICATION   a human relation between persons and things which emerges and is maintained through messages requiring and permitting not yet available encoding and decoding systems or mechanisms. Communication is a human relation between persons and things which emerges and is maintained through messages required and permitted by already available encoding and decoding systems or mechanisms. Communication feeds on an speeds the decay of information in systems on which depends the significance of human relations. Anticommunication not only retards this decay, but even creates systems whose significance depends on human relations. Insistence on communication ultimately leads to social and physical violence. Anticommunication ultimately leads to insistence on composition and peace. (Herbert Brun)

  The branch of computer science that studies how to program computers to exhibit apparently intelligent behavior. The branches of artificial intelligence are usually defined as pattern recognition, theorem proving, language processing, and game playing.

AUTHORITY   power conferred by agreement.

AUTOCATALYTIC   referring to something whose occurrence at one point increases the probability that it will occur again at another point. If a property of a system is autocatalytic, then such a system is, so far as that property is concerned, essentially unstable in its absence. (Ashby, 1956, p. 196) Examples: life on the planet Earth, guarantees of civil liberties in one nation among many, a product for which there is a demand. (Umpleby)

AUTOLETICS   The psychological principles and processes which underlie tasks in which performance appears to be self-rewarding.

That is, the task has the property of a goal rather than a means to a goal. Autotelic tasks are "intrinsically motivated." "Extrinsically motivated" tasks require external rewards. (James N. Mosel)

AUTONOMOUS   .independent in governing; mathematically when no factor in an equation contains time as an explicit variable. (Iberall)

AUTONOMY   the condition of subordinating all changes to the maintenance of the organization. Self-asserting capacity of living systems to maintain their identity through the active compensation of deformations. (Maturana and Varela, 1979)

AUTOPOIESIS   the process whereby an organization produces itself. An autopoietic organization is an autonomous and self-maintaining unity which contains component-producing processes. The components, through their interaction, generate recursively the same network of processes which produced them. An autopoietic system is operationally closed and structurally state determined with no apparent inputs and outputs. A cell, an organism, and perhaps a corporation are examples of autopoietic systems. See ALLOPOIESIS. (Francisco Varela)

  a machine organized (defined as a unity) as a network of processes of production, transformation and destruction of components that produces the components which: i) through their interactions and transformations regenerate and realize the network of processes (relations) that produced them; and ii) constitute it as a concrete unity in the space in which they exist by specifying the topological domain of its realization as such a network. (Maturana and Varela, 1979)

  an autopoietic organization constitutes a closed domain of relations specified only with respect to the autopoietic organization that these relations constitute, and thus it defines a space in which it can be realized as a concrete system, a space whose dimensions are the relations of production of the components that realize it. (Maturana and Varela, 1979)

  1. A branch of philosophy dealing with values, i.e., ethics, aesthetics, religion. Based on the Greek for "worth."
  2. The study of the nature of types of and criteria of values and of value judgments, especially in ethics (John Warfield)
  3. The general theory of value; the study of objects of interest. (Lotze)

  communication which travels through informal rather than formal channels. Governments and players in bureaucracies use back channel or informal communication to test reactions while maintaining deniability. (Prouty)

  1. any sequence of states of a system. (Ashby, Handout, 1961)
  2. The behavior of a system is overt and thus manifested in input-output relationships, whereas state trajectories are covert and must either be inferred or must be obtained by "opening the black box". (Michael Arbib)

BIFURCATION   a bifurcation is the appearance of an additional pattern of behavior or sequence of states for a system. Generally we have successive bifurcations where we increase the value of some characteristic parameter. One can think of a per-son traveling down a road. The farther the traveler goes, the more side streets or alternative routes appear. In a sense the bifurcation introduces history. To know the state of a system at any time implies a knowledge of the paths taken or not taken. (Umpleby after Prigogine, 1980, pp. 105-6)

BIOLOGICAL EXPLANATION   a reformulation in terms of processes subordinated to autopoiesis, that is a reformulation in the biological phenomenological domain. (Maturana and Varela, 1979)

BIOLOGICAL PHENOMENON   the biological phenomenology is the phenomenology of autopoietic systems in the physical space and a phenomenon is a biological phenomenon only to the extent that it depends in one way or another on the autopoiesis of one or more physical autopoietic unities. (Maturana and Varela, 1979)

BIONICS   an attempt to develop better machines through understanding of biological design principles. (DeGreene in Beishon and Peters, 3rd edition, pp. 92 and 94)

BORSODI's LAW   as the cost of production diminishes because of centralized operation, the cost of processing and distribution increases disproportionately. This law is prevalent especially for bulky and perishable commodities like foodstuffs, and where the fixed capital investment can be relatively low in proportion to the product as in natural farming. (Paul Goodman, "Notes on Decentralization," in BEYOND LEFT AND RIGHT).

BOUNDARY   The minimum description required to distinguish a system from its environment. (John Warfield)

BRAIN THEORY   The use of mathematics and computer simulation to analyze brain function. (Arbib)

  when a conflict over alternative policy proposals arises, they tend to be evaluated on the basis of the extent to which they imply an alteration in the relative power positions of the various subsystems affected. That decision is favored which least disrupts the existing balance of power among the subsystems. (Wheeler, 1970, p.133)

  very similar to INFORMATION PROCESSING CAPABILITY; the number of messages per unit time handled by either a link or a node (system, element). The messages transmitted may be either similar or different. It is usually measured in bits per second.

CLOSED SYSTEM   an isolated system having no interaction with an environment. (Von Bertalanffy, p.3)

CODING   The process of transforming information from one representation to another. Each way of representing information is called a code. (Arbib) A notion which represents the interactions of the observer, not a phenomenon operative in the observed domain. A mapping of a process that occurs in the space of autopoiesis onto a process that occurs in the space of human design (heteropoiesis) and, thus, not a reformulation of the phenomenon. (Maturana and Varela, 1979)

COGNITIVE DOMAIN   the domain of all the interactions in which an autopoietic system can enter without loss of identity. (Maturana and Varela, 1979)

COMBINATORIAL EXPLOSION   Occurs when a huge number of possible combinations are created by increasing the number of entities which can be combined--forcing us to consider a constrained set of possibilities when we consider related problems. (Arbib)

COMMUNICATION   a human relation between persons and things which emerges and is maintained through messages required and permitted by already available encoding and decoding systems or mechanisms. Communication feeds on and speeds the decay of information in systems on which depends the significance of human relations. See ANTICOMMUNICATION. (H. Brun)

COMMUNICATIVE DOMAIN   a chain of interlocked interactions such that although the conduct of each organism in each interaction is internally determined by its autopoietic organization, this conduct is for the other organism a source of compensable deformations. (Maturana and Varela, 1979)

COMPETITION   a type of activity existing among two or more elements of a system when each is striving to maximize its use of a finite and/or non-renewable resource. Agricultural land is an example of a finite, renewable resource. Mineral deposits are examples of finite, non-renewable resources. Competition for finite resources tends to accelerate rates of depletion or leads to overuse (see the tragedy of the commons). Overuse of finite, renewable resources can be corrected by altering the rewards and costs of marginal changes in use.

COMPOSITION   the composer's activity and the traces left by it. The composer's activity is motivated by a wish of bringing about that which without him and human intent would not happen. In particular, the composer's activity consists in constructing contexts, systems, stipulated universes, where in objects and statements, selected by the composer, not only manifest more than their mere existence, but have a function or value of sense or meaning which without his construction they would not have. Occasionally the composer's activity brings about that which without him and without human intent could not have happened, leaving traces which nothing else could have left. The wish which motivates the composer's activity is motivated by an exclusively human property which thus exhaustively and sufficiently defines the term "human": a "need" which is generated by a want. Among all biological systems only the human system contains that self-observing dimension when comes, beyond the system's "need," the system's want to survive. Thence the want, beyond the "need," of survival, and thus the exclusively human concept of an intent that would or will retard decay; in particular the decay of information, the ordering of a system, any system stipulated, discovered, or dreamed of. (H. Brun)

COMPUTER CONFERENCING   enables humans to conduct a conference even though widely scattered geographically, by communicating through a computer network. Each conferee has a MAILBOX--a reserved section of computer memory--to which messages may be sent by other conferees from their terminals. In addition to MESSAGES a computer conferencing system can include CONFERENCES and NOTEBOOKS. These are different ways of storing comments in computer memory and controlling who has access to the material.

CONCEPT   a word or phrase used in propositions purporting to describe real world relationships. Concepts are neither true nor false, only more or less useful. (Umpleby)

CONSEQUENCE   A consequence is a result of a COURSE OF ACTION (or of a decision) taken by the DECISION MAKER (Synonym: outcome; see IMPACT). In analysis, the consequences of a course of action are determined (predicted) by the use of MODELS. The consequences that one would like to have, particularly those that contribute positively to the attainment of OBJECTIVES, are referred to as [benefits;] the consequences that one would like to avoid or minimize are costs. The consequences that do not bear very much on the main objectives and are not evaluated in the analysis but that may affect the objectives of other groups of people are referred to as SPILLOVERS or EXTERNALITIES. A consequence tree is a graph showing what further consequences will be caused by some direct consequence of a course of action. For example, one alternative to stimulate the economy may be to lower taxes. This will result in an increase of average family income, which will in time influence the number of cars, which will have an impact on traffic conditions, on environmental pollution, and so on. In the literature on DECISION THEORY it is customary to speak about one [multiattribute consequence] of a course of action instead of saying "the action has several consequences." Accordingly, the term [single-attribute consequence] is used when the course of action has only one consequence that is being considered (e.g., monetary profit). Within the context of decision theory, attributes are those features of a consequence that are taken into account in the evaluation of this consequence by the decision maker. One speaks, more precisely, about [value-relevant attributes.] In mathematical formulations one speaks about a mapping from the space of courses of action (action space) into the space of consequences (consequence space.) In a deterministic case the mapping from action space to consequence space is a point-to-point mapping. This means that a given course of action has a given and certain consequence. In a case of RISK or UNCERTAINTY the mapping from action space to consequence space is a point-to-set mapping; that is, a given course of action may have any one of the consequences contained in a given set. In analysis, the mapping from action space to consequence space is described by a MODEL. (IIASA)

CONSTRAINT   a relation between two sets such that the variety that exists under one condition is less than the variety that exists under another. (Ashby, 1956 p. l27) The total variety possible is defined by the variables which were selected by the observer. Constraints reduce this variety to the variety actually observed. As Ashby says, "The cybernetician looks at what does not happen." The constraints, or the interaction rules operating over a set of variables, determine what does not happen. (Umpleby)

CONSTRAINT   .Constraints are limitations imposed by nature or by man that do not permit certain actions to be taken. Constraints may mean that certain OBJECTIVES cannot be achieved. The actions, ALTERNATIVES, CONSEQUENCES, and objectives that are not precluded by the constraints are referred to as [feasible.] In a particular analysis study, some constraints may have to be considered [stiff] or unquestionable, others--from among those imposed by prior decisions--may be [elastic] or removable if the analysis proves a good case for it. For example, the natural water supply in a region is a stiff constraint, while the money or manpower allocated to fulfill a certain task may be an elastic constraint. It is useful to distinguish [short-run] and [long-run] constraints: for example, existing legislation is a constraint in the short run, but not necessarily in the long run. In mathematical terms, if the notions of ACTION SPACE, CONSEQUENCE SPACE, and OBJECTIVE SPACE are introduced, the constraints determine a [feasible set] in each of those spaces. (IIASA)

CONTEXT   The material that surrounds an item which helps define its meaning. (Arbib)

CONTINGENCY ANALYSIS   Contingency analysis is a method of treating UNCERTAINTY that explores the effect on the ALTERNATIVES of change in the ENVIRONMENT in which the alternatives are to function. This is a "what-if" type of analysis, with the what-ifs being external to the alternative, in contrast to a SENSITIVITY ANALYSIS, where the parameters of the alternatives are varied. See also: A FORTIORI ANALYSIS. (IIASA)

CONTINUUM   a space or field whose elemental parts cannot be separately discerned at the scale of observation. (Iberall)

CONTROL   Choosing the inputs to a system so as to make the state or outputs change in (or close to) some desired way. (Arbib)

COOPERATION   a type of activity existing among two or more elements of a system when they are engaged in a mutually beneficial exchange.

CORRESPONDENCE PRINCIPLE   any new theory, whatever its character--or details--should reduce to the well-established theory to which it corresponds when the new theory is applied to the circumstances for which the less general theory is known to hold. This principle was first applied to the theory of atomic structure by Niels Bohr in l923. (Weidner and Sells, l960, p. 29) The principle can be applied to great advantage in relativity theory and in quantum mechanics. It can also be applied to the LAW OF REQUISITE VARIETY, the PRINCIPLE OF SELF-ORGANIZATION, and the more recent interpretations of the possibility of objectivity. (Umpleby)

COUPLED   When mechanisms or functional subsystems are connected causally to influence each other, they are said to be coupled. If A is causally connected to B, the connection is often described by coupling coefficients or influence coefficients. (Iberall)

  whenever the conduct of two or more unities is such that the conduct of each one is a function of the conduct of the others. (Maturana and Varela, 1979)

COURSE OF ACTION   A means available to the DECISION MAKER by which the OBJECTIVES may be attained. A SYSTEMS ANALYSIS usually considers several possible courses of action, which are then referred to as ALTERNATIVES or as the decision maker's OPTIONS. (IIASA)

CREOD   derived from the Greek words for "necessity" and "a path." A term coined by D.S. Waddington who says a creod is a "time trajectory of developmental change (arising) from the characteristics of the closed circular causal organization of the system of genes and cytoplasm. Creods are a type of phenomena which occurs in many other fields also." (Waddington, 1960, p. 82)

CRITERION   A criterion is a rule or standard by which to rank the ALTERNATIVES in order of desirability. The use of "criterion" to mean "objective" is incorrect. See OBJECTIVE. (IIASA)

  1. The science of communication and control in animal and machine.
  2. Perhaps because the field is still young, there are many definitions of cybernetics. Norbert Wiener, a mathematician, engineer and social philosopher, coined the word "cybernetics" from the Greek word meaning steersman. He defined it as the science of communication and control in the animal and the machine. Ampere, before, him, wanted cybernetics to be the science of government. For philosopher Warren McCulloch, cybernetics was an experimental epistemology concerned with the communication within an observer and between the observer and his environment. Stafford Beer, a management consultant, defined cybernetics as the science of effective organization. Anthropologist Gregory Bateson noted that whereas previous sciences dealt with matter and energy, the new science of cybernetics focuses on form and pattern.
  3. A way of looking at things and a language for expressing what one sees (Margaret Mead)

  1. an organism with a machine built into it with consequent modification of function;
  2. an organism which is part animal and part machine. Since some theorists regard organisms as biological machines, we must define our terms further. An animal will be defined as a creature whose elements are the result of "small loop autopoiesis." That is the creature creates itself but the parts are the result of localized processes. Mind is not involved in the production of the parts. Mind results from the functioning of the parts but is manifested in the external behavior of the organism. A cyborg, then, is a creature composed of some parts constructed without the benefit of mind and some parts constructed with the benefit of mind. Furthermore the parts must be of greater than molecular size. A creature with aspirin in its body is not a cyborg. A creature with an artificial heart is a cyborg. Under this definition, animals with donated hearts, kidneys or retinas would also be cyborgs. (Umpleby)

DECENTRALIZED GOVERNMENT   A form of government with its top-level decision-making processes dispersed throughout the system rather than concentrated in one person, place or legislative body. (Arbib)

DECISION MAKER   A decision maker is a person, or group of people (e.g., a committee), who makes the final choice among the ALTERNATIVES. Synonym: decision taker. (IIASA)

DECISION THEORY   Decision theory is a body of knowledge and related analytical techniques of different degrees of formality designed to help a DECISION MAKER choose among a set of ALTERNATIVES in light of their possible CONSEQUENCES. Decision theory can apply to conditions of certainty, RISK, or UNCERTAINTY. [DECISION UNDER CERTAINTY] means that each alternative leads to one and only one consequence, and a choice among alternatives is equivalent to a choice among consequences. In [DECISION UNDER RISK] each alternative will have one of several possible consequences, and the probability of occurrence for each consequence is known. Therefore, each alternative is associated with a probability distribution, and a choice among probability distributions. When the probability distributions are unknown, one speaks about [DECISION UNDER UNCERTAINTY.] Decision theory recognizes that the ranking produced by using a CRITERION has to be consistent with the decision maker's OBJECTIVES and preferences. The theory offers a rich collection of techniques and procedures to reveal preferences and to introduce them into MODELS of decision. It is not concerned with defining objectives, designing the alternatives or assessing the consequences; it usually considers them as given from outside, or previously determined. Given a set of alternatives, a set of consequences, and a correspondence between those sets, decision theory offers conceptually simple procedures for choice. In a decision situation under certainty the decision maker's preferences are simulated by a single-attribute or MULTIATTRIBUTE VALUE FUNCTION that introduces ordering on the set of consequences and thus also ranks the alternatives. Decision theory for risk conditions is based on the concept of utility (see UTILITY, sense 2). The decision maker's preferences for the mutually exclusive consequences of an alternative are described by a UTILITY FUNCTION that permits calculation of the EXPECTED UTILITY for each alternative. The alternative with the highest expected utility is considered the most preferable. For the case of uncertainty, decision theory offers two main approaches. The first exploits criteria of choice developed in a broader context by GAME THEORY, as for example the [MAX-MIN RULE,] where we choose the alternative such that the worst possible consequence of the chosen alternative is better than (or equal to) the best possible consequence of any other alternative. The second approach is to reduce the uncertainty case to the case of risk by using SUBJECTIVE PROBABILITIES, based on expert assessments or on analysis of previous decisions made in similar circumstances. See also: GAME THEORY, OPTIMIZATION, UTILITY, VALUE (IIASA)

  1. A group communication structure used to facilitate communication on a specific task. The method usually involves anonymity of responses, feedback to the group as a whole of individual and/or collective views and the opportunity for any respondent to modify an earlier judgment. The method is usually conducted asyncronously via paper and mail but can be executed within a computerized conferencing environment. At the essence of the method is the question of how best to tailor the communication process to suit the situation. The Delphi method was originally developed at the RAND Corporation by Olaf Helmer and Norman Dalkey. (Murray Turoff)
  2. A technique to arrive at a group position regarding an issue under investigation, the Delphi method consists of a series of repeated interrogations, usually by means of questionnaires, of a group of individuals whose opinions or judgments are of interest. After the initial interrogation of each individual, each subsequent interrogation is accompanied by information regarding the preceding round of replies, usually presented anonymously. The individual is thus encouraged to reconsider and, if appropriate, to change his previous reply in light of the replies of other members of the group. After two or three rounds, the group position is determined by averaging. (IIASA)

  1. As a term in economics, demand means the amount of a commodity (good or service) that would be purchased at a given price. An associated term is [DEMAND FUNCTION,] which presents the demand-versus-price relationship. A demand function for a given commodity is compared with a corresponding [SUPPLY FUNCTION] to determine the EQUILIBRIUM PRICE: a price at which the supply offered matches the demand.
  2. In another usage, demand means the amount of a commodity required for a certain purpose. It often relates to the future, as in: "the world energy demand in the year 2030 will be 35 terawatts." Implicit in this statement is that the price of energy as well as other economic conditions will be such that 35 terawatts will be consumed (purchased) if technically available. (IIASA)

DIALECTIC   The Hegelian method of logic, based on the concept of advancing contradictory arguments, of thesis and antithesis, and seeking their resolution by synthesis. (Iberall)

DIFFUSION   the spread of an idea, product or process beyond first use. (Umpleby)

DISCOUNT RATE   It is assumed that a monetary unit received today is worth more than a monetary unit to be received a year from now. This assumption requires that, in order to determine the present value of future sums, the analyst use an interest rate to discount these future sums. If i is the assumed annual interest or discount rate, expressed as a decimal, the present value of x monetary units to be received in n years from now is given by the formula:

     Present value =       X

Discount rates are used when comparing alternatives that differ in the time-character of their flows of COSTS and BENEFITS; to compare them, costs and benefits are discounted to the same year. There are no clear-cut rules as to what an appropriate discount rate should be in a given case.

DISCOUNTING   The process by which most people place a heavy emphasis on the present and very near future and by which events not in the present or very near future are not considered important for consideration, i.e., are discounted. (Rogers)

DIVERSITY   variations in the mode in which identity is maintained. (Maturana and Varela, 1979)

DOMAIN   Generally a limited region or field marked by some specific property. In mathematics, it can have a somewhat more specialized meaning. (Iberall)

DOMINANCE   An ALTERNATIVE is said to be dominant with respect to a second alternative whenever one or more of the CONSEQUENCES of the first are superior (i.e., preferred according to some CRITERION) to the corresponding consequences of the second, and all others are equally valued. (IIASA)

ECONOMY OF SCALE   Relative saving realized when the size of a plant, enterprise, etc., is increased. For example, lower production cost of an automobile due to production of a large number of cars of the same type is due to economy of scale. There may also exist a DISECONOMY OF SCALE where the increased size contributes to an increase in unit cost.

  1. In SYSTEMS ANALYSIS, the effectiveness of an ALTERNATIVE is usually represented by an aggregative expression approximating the totality of output or performance aspects of that alternative that are relevant to goal attainment. Ideally, it is a single quantitative measure that can be used to evaluate the performance level achieved in attaining the OBJECTIVES. (IIASA)
  2. An absolute measure of performance. (Turoff)

  1. Program A is said to be more efficient than program B if, for a given cost, a chosen aggregated measure of its positive results (such as EFFECTIVENESS or BENEFIT) is greater than that for program B. (IIASA)
  2. A ratio scale measurement of a measure of performance to resources expended to obtain the level of performance. (Turoff)

ENSEMBLE   An aggregation or collection of elements connected by a series of relations. (Iberall)

ENTROPY   unavailable energy or molecular disorder. Entropy is at a maximum when the molecules in a gas are at the same energy level. Entropy should not be confused with uncertainty. Uncertainty is at a minimum when all elements are in the same category. (Umpleby)

ENVIRONMENT   Environment is most often used as a synonym of state of nature, a concept useful in modeling. It embraces all external factors or forces that are beyond the influence of the DECISION MAKER but nevertheless affect the CONSEQUENCES of his action. Environment is also occasionally used as a synonym of STATE OF THE WORLD. The difference between the two concepts is that state of the world can include the consequences of a course of action as well as the external factors, while the state of nature comprises the external factors only (IIASA)

EPIGENETIC   Related to the doctrine that the entity that will develop into a viable system (e.g., the germ cell developing into an organism) is acted upon and depends both on the conditions in its environment as well as its internal coding (i.e., it is both the phenotype and genotype that determines the emergence of the living organism). (Iberall)

EQUIFINALITY   a condition in which different initial conditions led to similar effects. (see MULTIFINALITY.) Equifinality in biological systems led the German biologist Driesch to embrace vitalism--the doctrine that vital phenomena are inexplicable in terms of natural science. (Von Bertalanffy, p. 40)

EQUILIBRIUM   a condition characterized by a balance of forces. (Umpleby)

  1. of or relating to a process in which a sequence or sizable sample is equally representative of the whole (as in regard to a statistical parameter);
  2. involving or relating to the probability that any state will recur, especially having zero probability that any state will never recur. (WEBSTER'S DICTIONARY)

ERGODIC   A collection of systems forms an ergodic ensemble if the modes of behavior found in any one system from time to time resemble its behavior at other temporal periods and if the behavior of any other system when chosen at random also is like the one system. We do not require identical performance, only quite similar time averages and number averages. (If you cannot tell one youth from another or one adult from another, they belong to an ergodic ensemble.) In an ergodic population, any single individual is representative of the entire population. The salient characteristics of this individual are essentially identical with any other member of the group. (Iberall)

ETHOLOGY   The newer definition relates to the study of animal behavior, founded on a comparative zoological and physiological base. (Iberall)

EUDEMONY   a measure of the more preferred state of affairs; the commodity that the control system tends to optimize. The eudemony concern is one of values, of stating what is worth optimizing; in short, eudemony is a category of outcomes that indicate we are enhancing the quality of life. (Beer, PLATFORM FOR CHANGE, p. l59)

EVALUATION   Evaluation as used in a technical sense in the United States means assessment of a government program's past or ongoing performance. The key issue in PROGRAM EVALUATION is to determine the extent to which the program, rather than other factors, has caused any changes that have been observed. (IIASA)

EVIDENCE   a configuration (a human made image) of reality used and an "argument" in support of the reality of this configuration. I use the word "evidence" only rarely, and then with embarrassment. Samefacedly I am forced to admit that I am a member, and speak the languages, of such societies as must not yet be encouraged to waive the "argument" and to deal directly with the configuration as the only reality worth dealing with. Not yet: because "evidence," now, is reality against change, and change, now, reality against "evidence." Shamefacedly: because, as long as the word which I wish to define, defines me, I cannot define it, without defining myself, whom I desire to be defined quite differently. Worth dealing with: because, even then, "truth" would not be. I wish I could use the word "evidence" whenever I wish to speak of "desires" fulfilled, and the consequences, as "arguments" for or against the desirability of the fulfillment. (H. Brun)

  1. A process of continuous change from a lower, simpler, or worse, to a higher, more complex, or better state; a process of change in some direction. (Webster's)
  2. The coming into being of a new and higher order process. (Laszlo)
  3. The development of each species from different, usually simpler ancestral forms. The more similar are two species, the closer in time are they likely to be to a common ancestor. (Arbib)
  4. history of change in the realization of an invariant organization embodied in independent unities sequentially generated through reproductive steps, in which the particular structural realization of each unity arises as a modification of the preceding one (or ones) which, thus, constitutes both its sequential and historical antecedent. (Maturana and Varela, 1979)

EXPANSIONISM   A doctrine that maintains that all objects, events and experiences are parts of larger wholes. Expansionism is another way of viewing things, a way that is different from, but compatible with, reductionism. (Ackoff, l974, p. l2)

EXPERIMENTATION   In SYSTEMS ANALYSIS, experimentation is the process of determining the results of a proposed COURSE OF ACTION or program by conducting an experiment on a smaller scale in which the course of action is applied to a sample drawn from the future target group. An example would be a test of a new health policy in a restricted region instead of the whole country, or a test on a randomly selected sample of the population. The results are best when the experiment is controlled--i.e., when the test and control groups are chosen before program implementation in such a way that they are as similar as possible. In this way, any differences that are observed during the experiment can be ascribed to the program. Experimentation is used whenever current knowledge and understanding of factors such as social attitudes and group preferences are not sufficient to provide dependable model-based predictions. (See: MODEL) (IIASA)

EXPLANATION   a reformulation of a phenomenon in such a way that its elements appear operationally connected in its generation. (Maturana and Varela, 1979)

EXTERNALITY   An externality is a CONSEQUENCE not considered in analysis. An externality that affects the interests of other groups of people or other DECISION MAKERS is referred to as a SPILLOVER. If the effects of an externality are appreciable, it may have to be taken into account (internalized) in the analysis. The term externality derives from economics, where externalities are costs or benefits not taken into account in a transaction or system of transactions. For example, the cost borne by others when an industry pollutes a stream would be referred to as an externality. (IIASA)

FAIL SAFE   a property of a system in which failure is impossible. See SAFE FAIL.

FEEDBACK   information about the results of a process which is used to change the process itself. Negative feedback reduces the error or deviation from a goal state. Positive feedback increases the deviation from an initial state. (Umpleby)

FLUCTUATION   the change in some physical quantity in time, particularly if it varies around some average value for the quantity. (Iberall)

FORECAST   A forecast is a statement, usually in probabilistic terms, about the future state or properties of a system based on a known past and present. A CONDITIONAL FORECAST states in probabilistic terms what the future will be if a course of action is taken. A forecast that states with a high degree of confidence what the future will be is referred to as a PREDICTION. A forecast that is a hypothesis rather than a formally justified inference from past data is referred to as a SCENARIO. Forecasting techniques range from expert judgments to mathematical forecasting MODELS. The FORECASTING LEAD (forecasting horizon) is the length of time ahead of now for which one can make a reasonable forecast. It depends, in the general sense, on available data. A forecast that makes itself come true is referred to as a SELF- FULFILLING FORECAST. For example, a forecast for the rapid growth of a certain city may encourage business to locate there, thus causing the forecast to be realized. (IIASA)

FREEDOM   Every social system grants its members some freedom. Freedom consists of the kind and number of alternatives open for choice to its members. However, every choice made leads to a loss of freedom: the structure of these systems tends, in consequence of the choice made to render at least some not chosen alternatives, from then on, inaccessible to the members who made the choice. The freedom granted therefore reduces the freedom of those of its members who use it. Choice results in loss of freedom. Loss of freedom can only be prevented by a society so structured, that it would remain desirable to its members, even if, therein, the freedom of choice were never to reduce, at least to preserve, and often to increase, the number of alternatives open for choice. (H. Brun)

  1. Metaphor, that image which determines another image. (Rogers)
  2. An association of a certain object(s) from one set with each object from another set (mathematics). (Rogers)
  3. The normal or characteristic action of a system of entities, generally in time. (Iberall)
  4. The variation of some magnitude that depends upon the variation of some other magnitude. (Iberall)
  5. a notion that arises in the description made by the observer of the components of a machine or system in reference to an encompassing entity, which may be the whole machine or part of it and whose states constitute the goal that the changes in the components are to bring about. (Maturana and Varela, 1979)

GAME   a set of moves which are defined by a set of rules limiting what the players may do. A game may or may not be a simulation. A game does not necessarily involve a representation of events in a reference system. (Umpleby)

GAME THEORY   Game theory is a branch of mathematical analysis developed to study decision making in conflict situations. Such a situation exists when two or more DECISION MAKERS who have different OBJECTIVES act on the same system or share the same resources. There are two person and multiperson games. Game theory provides a mathematical process for selecting an OPTIMUM STRATEGY (that is, an optimum decision or a sequence of decisions) in the face of an opponent who has a strategy of his own.

In game theory one usually makes the following assumptions:

  1. Each decision maker ["PLAYER"] has available to him two or more well-specified choices or sequences of choices (called "PLAYS").
  2. Every possible combination of plays available to the players leads to a well-defined end-state (win, loss, or draw) that terminates the game.
  3. A specified payoff for each player is associated with each end-state (a [ZERO-SUM GAME] means that the sum of payoffs to all players is zero in each end-state).
  4. Each decision maker has perfect knowledge of the game and of his opposition; that is, he knows in full detail the rules of the game as well as the payoffs of all other players.
  5. All decision makers are rational; that is, each player, given two alternatives, will select the one that yields him the greater payoff.

The last two assumptions, in particular, restrict the application of game theory in real-world conflict situations. Nonetheless, game theory has provided a means for analyzing many problems of interest in economics, management science, and other fields. (IIASA)

  1. A structure, configuration, or pattern of physical, biological, sociological, or psychological phenomena so integrated as to constitute a functional unit with properties not derivable from its parts in summation. This German word is considered by many system thinkers (e.g., von Bertalanffy, Angyal) to convey more accurately the concept of organized wholes than the word system. (Steven Rogers)
  2. The organized structure or pattern that makes up all of a person's experience of some system. This integrated view is more than the sum of the individual elements by which the field can be described. (Iberall)

  1. End toward which effort is directed. (Webster's)
  2. A statement, expressed in the following form: To (Action Word) (Object) (Qualifying Phrase). (John Warfield)
  3. A preferred outcome in a particular situation that can be obtained within a specified time period. (Ackoff)
  4. An end state consciously selected a priori. (Larry Richards)

GOAL SEEKING   the process of arriving at a goal once it has been defined. (Umpleby)

  the process of deciding what the next goal to be sought will be. (Umpleby)

HERMENEUTIC   interpretive; explanatory.

HERMENEUTICS   plural in form, used with a singular verb. The science and methodology of interpretation, especially of Scriptural text. From the Greek "to interpret."

HETEROPOIESIS   the space of human design. (Maturana and Varela, 1979)

HETERARCHY   a form of organization resembling a network or fishnet. Authority is determined by knowledge and function. See HIERARCHY. (Umpleby)

  1. Characterizing a system in which the internal parameters can be changed when necessary through feedback.
  2. A heuristic idea serves as a guide for discovery. It serves as a valuable aid for empirical research but may be unproved or incapable of proof. (Umpleby)

HEURISTIC   An aid to discovery, any device or procedure used to reduce problem-solving effort, a rule of thumb.

  1. A form of organization resembling a pyramid. Each level is subordinate to the one above it. See HETERARCHY. (Umpleby)
  2. An organization whose components are arranged in levels from a top level down to a bottom level. (Arbib)
  3. A partially-ordered structure of entities in which every entity but one is successor to at least one other entity; and every entity except the basic entities is a predecessor to at least one other entity. (Rogers)
  4. Narrowly, a group arranged in order of rank or class; we interpret it to denote a rank arrangement in which the nature of function at each higher level becomes more broadly embracing than at the lower level. (Iberall)

HISTORICAL PHENOMENON   a process of change in which each state of the successive states of a changing system arises as a modification of a previous state in a causal transformation and not de novo as an independent occurrence. (Maturana and Varela, 1979)

HOLISM   the process of focusing attention directly on the whole and its characteristics as a whole, without any recourse to consideration of its parts. (Sahal, in FUTURE DIRECTIONS, or Lendaris and Wakeland, "Structural Modeling - A Bird's Eye View")

  1. Dynamic self-regulation.
  2. The condition of a system when it is able to maintain its essential variables within limits acceptable to its own structure in the face of unexpected disturbances. The concept was formulated by W.B. Cannon in 1929-32.

HOMEOSTAT   a machine built by Ross Ashby in the l940's to demonstrate the behavior of an ULTRASTABLE SYSTEM. For a description, see Chapter 8 of Ashby, 1960.

  machines which display the condition of maintaining constant or within a limited range of values some of their variables. (Maturana and Varela, 1979)

HOMOMORPHISM   similarity of external form, appearance or size.

  1. the representation of ideas by graphic symbols.
  2. the use of ideograms to express ideas.

IMPACT   Impact is used in three different ways:

  1. as synonymous with CONSEQUENCE;
  2. to mean any consequence (beneficial or adverse) that reaches beyond the direct purpose of a given COURSE OF ACTION, as in: "the impact of the new steel plant on employment opportunities in the region;"
  3. as in (2), but the meaning restricted to adverse consequences, as in "the impact of industrial growth on the ecological environment." (IIASA)

IMPLEMENTATION   Implementation means the process of carrying out a course of action. Implementation starts at the decision and terminates when the objectives are attained. (IIASA)

INDIVIDUALITY   maintenance of identity by an autopoietic machine independently from its interactions with an observer. (Maturana and Varela, 1979)

  1. that which reduces UNCERTAINTY. (Claude Shannon);
  2. that which changes us. (Gregory Bateson)

INFORMATION ENVIRONMENT   the messages, symbols, meanings, that a person encounters in an average day through conversations with other persons and through the media. People inhabiting nearly the same physical environment can live in very different information environments. An example would be people working on a university campus or in an international organization.

INPUT   an event external to a system which modifies the system in any manner.

  Input-output (Leontief) analysis is a technique developed for quantitatively analyzing the interdependence of producing and consuming units in an economy. Input-output analysis studies the interrelations among producers as buyers of each other's outputs, as users of resources, and as sellers to final consumers. For example, if a planner wishes to expand the activities of some industry, or some component of final consumption, an input-output analysis can tell what amount of other manufactured goods, resources, and labor this requires. In an INPUT-OUTPUT MODEL the output product of each sector of the economy is set equal to the input consumption of that product by other industries plus the consumption by final consumers. All inputs and outputs are expressed in the same units (usually in monetary units per unit of time, for example in schillings/year). One denotes Aij the worth of output product of sector i required as input by sector j to produce one unit's worth of its product. Then, if we denote Xl, X2,..Xn the output products of the sectors, the basic relation of the MODEL is:

               Xi   =    SUM  Aij Xj  +  Yi

where Yi is the consumption of product i by final consumers. In a model with three sectors, we have, for example, for the output product X2:

X2 = A2l Xl + A22 X3 + Y2

>which reads: "out of the total output X2 the amount A2l Xl is used by sector l to produce output Xl,..., and the amount Y2 is consumed by final consumers." The parameters Aij are referred to as TECHNOLOGICAL COEFFICIENTS. They are usually arranged into a table called the TECHNOLOGICAL INTERDEPENDENCE MATRIX for the system being modeled. (IIASA)

INQUIRING SYSTEM   An orderly and fully developed procedure or plan for investigation. Philosophically, a way of looking at reality. Frequently used to describe the formal methodologies of the major philosophers. The term implies adherence to rigid set of procedures that are uniquely derived from a single, fundamental concept of reality. (Example: one who believes that truth and knowledge are only derived from experience would base an investigation upon experimental procedures and would not rely upon analysis or synthesis to extrapolate from one piece of knowledge to another.) (Mitroff and Turoff)

INTELLIGENCE   Appropriate selection. (Ross Ashby)

  1. The immediate knowing or learning of something without the conscious use of reasoning. (Webster's)
  2. In its cognitive function it is a psychic organ or means to apprehend reality. It is a synthetic function in the sense that it apprehends the totality of a given situation or psychological reality. It does not work from the part to the whole -- as the analytical mind does -- but apprehends a totality directly in its living existence. (Assagioli)
  3. It is by logic that we prove, but by intuition that we discover. (Poincare, CY sq.)

ISOMORPHIC   Having the same or similar form; we have interpreted this more broadly to represent similarity in both form and function. (Iberall)

  1. A mapping of one entity into another having the same elemental structure, whereby the behaviors of the two entities are identically describable. (John Warfield)
  2. A formal correspondence of general principles or even of special laws. (Bertalanffy)
  3. A set of principles may be transferred from one field to another without need to duplicate the effort. (Weinberg)
  4. a one-to-one correspondence between the elements of two sets such that the result of an operation on elements of one set corresponds to the result of the analogous operation on their images in the other set.

ITERATIVE PROCESS   An iterative process is a process for calculating a desired result by means of a repeated cycle of operations. An iterative process should be convergent, i.e., it should come closer to the desired result as the number of iterations increases.

JUMP PHENOMENA   In many fields, there are surfaces of discontinuity on both sides of which the field phenomena change drastically. The change in conditions between the two sides is said to be described as a jump and represents jump phenomena. (Iberall)

KLUGE   something not designed as a whole but rather put together from available parts. The term if frequently used by engineers. Marvin Minsky has described the human brain as a kluge.

LANGUAGE   A systematic way of arranging symbols, usually to express meaning. It may be a NATURAL LANGUAGE like Chinese, English or Swahili that humans use to communicate with one another, or a PROGRAMMING LANGUAGE in which programs are written for a computer. (Arbib)

LAW OF REGULATORY MODELS   every good regulator of a system must be (contain) a model of that system. (Conant and Ashby, 1982)

  1. the amount of appropriate selection that can be performed is limited by the amount of information available.
  2. for appropriate regulation the variety in the regulator must be equal to or greater than the variety in the system being regulated. Or, the greater the variety within a system, the greater its ability to reduce variety in its environment through regulation. Only variety (in the regulator) can destroy variety (in the system being regulated). The law was formulated by Ross Ashby. (Umpleby)

LIMIT CYCLE   In a linear system (such as a vibrating string or a pendulum), if the system is displaced (pluck the string), it will start to vibrate or oscillate. However, according to the second law of thermodynamics the system will decay to rest. In a nonlinear system (examples: a watch, a human, a working engine) supplied with a constant source of fuel or energy, it is possible to obtain configurations such that if the system is started vibrating, oscillating, or running, it will continue. If the cycle thus formed operates independent of the precise initial starting conditions, in spite of the fact that the system is loggy and in spite of moderate disturbances that tend to slow the process down or speed it up, then it is said to be a limit cycle. (Iberall)

LINGUISTIC DOMAIN   a consensual domain in which the coupled organisms orient each other in their internally determined behavior through interactions that have been specified during their coupled ontogenies. (Maturana and Varela, 1979)

LINGUISTICS   The study of language. This includes the study of syntax -- what it is that makes a sentence well-formed -- and of semantics -- how the words of a sentence work together to give the sentence its overall meaning. Parsing is the process of breaking a string of words into the constituents specified by the syntax. (Arbib)

  1. a state-determined system; any system showing behavior such that the specification of a state determines the subsequent state; a set of states closed under a mapping. (Ashby, Handout, l96l)
  2. a unity in the physical space, defined by its organization, which connotes a non-animistic outlook, and whose dynamisms are apparent. (Maturana and Varela, 1979)

  any machine in which part of the state vector is regarded as under exterior control (the input) and part inaccessible (the internal state) such that for any pairing of input and internal state, the subsequent internal state is determined. (Ashby, Handout, l96l)

  the use to which a machine can be put by man, sometimes its product. A descriptive device to reduce the task of conveying to a listener the organization of a particular machine. (Maturana and Varela, 1979)

MARGINAL EFFECTIVENESS   ratio of the increase in performance due to an increase in the resources expended. (Turoff)

  a probabilistic machine; any system showing behavior such that the probability (frequency) of any given state determines the probability (frequency) of the subsequent state; any machine in which the states are given as probabilities. (Ashby, Handout, l96l)

MECHANICAL PHENOMENOLOGY   the phenomenology generated by relations between processes realized through the properties of components. (Maturana and Varela, 1979)

MECHANISM   a biological outlook which asserts that the only factors operating in the organization of living systems are physical factors, and that no non-material vital organizing force is necessary. (Maturana and Varela, 1979)

MEDIATE   To be the intermediate mechanism for bringing about change or providing communication; i.e., to manipulate to new operating conditions. (Iberall)

METAPHOR   a figure of speech in which a term is transferred from the object it ordinarily designates to an object it may designate only by implicit comparison or by analogy, as in the phrase "evening of life."

META-SYSTEM   a system acts according to its own nature and for the purpose defined by that nature. A child is playing: he attempts to poke scissors into the electric power points; he makes interesting ink-patterns on the carpet; he attempts to drink from the liquid detergent container. All of these activities arise directly from the nature of the system: child - exploration -environment. Fortunately there is another system which lies outside the child system. This outside or meta-system operates according to its own nature which is child care. Primitive tribes quickly establish a system of beliefs, taboos and laws. Without this meta-system everyone would act according to their own individual systems which might be based on immediate gratification, self-indulgence and impulse. The meta- system lies outside these individual systems and overrides them in favor of society and a longer time base. For example, an individual may only collect enough food for his immediate needs but the meta-system may require him to collect enough to store for the winter as well. To some extent, the success of societies has depended on the strength, and the nature, of the meta-systems they have set up. An individual goes to see a psychoanalyst and is told that his troubles arise from the way his mother treated him when he was young. This explanation or 'story' becomes a meta-system for the individual and can explain or guide his actions independently of his mood of the moment. Religion is the prime example of a meta-system that has served to override man's small view of himself and given him aims and values he might not otherwise have developed. The internal logic of the religious meta-system is based on its own nature,and not on the needs of man. Outside religions, strictly so called ideologies, philosophies and moral concepts have also served as meta-systems. (De Bono)

METHODOLOGY   The systematic analysis and organization of the rational and experimental principles and processes which must guide a scientific inquiry, or which constitute the structure of the sciences more particularly. Methodology is a generic term exemplified in the specific method of each discipline and its full significance can be understood only by analyzing the structure of each discipline. In determining that structure, one must consider

(a) the proper object of the discipline,

(b) the manner in which it develops,

(c) the type of statements or generalizations it involves,

(d) its philosophical foundations or assumptions, and

(e) its relation with other disciplines and eventually its applications. (Dict. of Philosophy)

A methodology is a kind of "coaching" -- not a formula for producing a result, but a set of practices that can lead to appropriate questioning and to appropriate change. (Winograd and Flores, 1987)

MICROWORLD   a limited "world" - such as the subject matter of a specialized data base - that restricts the semantics of a computer program for planning or natural language understanding. (Arbib)

MILIEU   Surroundings, environment, in the sense of a fluid-like environment in which many diverse species or biota are immersed. (Iberall)

MINIMAX PRINCIPLE   in situations with conflicting alternatives, the most rational strategy is the one that promises to minimize the maximum possible losses.

MODEL   a set of propositions or equations describing in simplified form some aspects of our experience. Every model is based upon a theory, but the theory may not be stated in concise form. (Umpleby)

MODEL   An object or process which shares crucial properties of an original, modeled object or process, but is easier to manipulate or understand. A SCALE MODEL has the same appearance as the original save for size and detail. However, increasing use is made of COMPUTER SIMULATION: the model is a program that enables a computer to determine how key properties of the original will change over time. It is easier to change a program than to rebuild a scale model if we want to explore the effect of changes in policy or design. (Arbib)

MODEL   A model is a device, scheme, or procedure typically used in SYSTEMS ANALYSIS to predict the CONSEQUENCES of a COURSE OF ACTION; a model usually aspires to represent the real world (to the degree needed in analysis)--for example, a relation between some observed phenomena. A model can be FORMAL (e.g., a mathematical expression, a diagram, a table) or JUDGMENTAL (e.g., as formed by the deductions and assessments contained in the mind of an expert). Some models are CAUSAL -- i.e., they reflect cause-effect relationships. Others are CORRELATIONAL MODELS which do not necessarily reveal whether some of the observed phenomena are the cause of the others. An example is correlation models used for weather forecasting; note that the farmer who predicts rain on the basis of some observed phenomena and his past experience is using a judgmental correlation model. A DETERMINISTIC MODEL generates the response to a given input by one fixed law; a STOCHASTIC MODEL picks up the response from a set of possible responses according to a fixed probability distribution (stochastic models are used to simulate the behavior of real systems under random conditions). A DYNAMIC MODEL can describe the time-spread phenomena (dynamic processes) in a system. A STATIC MODEL describes the system at a given instant of time and in an assumed state of equilibrium. Among the formal, mathematical models an ANALYTIC MODEL is formed by explicit equations. It may permit an analytic or numerical solution. An analytic model is LINEAR if all equations in the model are linear. We speak of a SIMULATION MODEL if the solution, i.e., the answer to the question which the analyst has posed, is obtained by experiments on the model rather than by an explicit solution algorithm. A typical example is STOCHASTIC SIMULATION, where one wants to obtain probabilistic properties of a system's response by evaluating the results of a large number of simulation runs on the model. In some analyses the model by which one predicts the outcome of a course of action must take into account that this outcome depends also on actions taken by other decision makers. If the assumption can be made that those decision makers optimize some defined objective functions, and all the other aspects of the system can also be formalized, an OPTIMIZATION MODEL (e.g., a linear programming model) can be used to determine the system's response to a course of action. In ROLE-PLAYING MODELS those decision makers (and perhaps some other elements of the system as well) are simulated by human actors. In a MAN-MACHINE MODEL an actor or actors play roles while other parts of the model are implemented on a computer. A formal model has a STRUCTURE (the form of an equation, for example) and PARAMETERS (the value of coefficients in an equation for example). Determination of both the structure and parameters is MODEL IDENTIFICATION; determination of the parameters on the basis of experimental data is MODEL ESTIMATION. The check of a proposed model against experimental data other than those used for parameter estimation is model VALIDATION. See also VERIFICATION. (IIASA)

MODEL OF THE WORLD   The information that an animal or robot has stored about the world around it. It thus serves to guide the system's interaction with its environment. (Arbib)

  1. evolutionary development of the structure of an organism or part.
  2. embryological development of the structure of an organism or part.
  3. The process in complex system-environment exchanges that tends to elaborate a system's given form or structure. Examples are the growth of an animal from a fertilized ovum, biological evolution, learning, and societal development. A morphogenic system is capable of maintaining its continuity and integrity by changing essential aspects of its structure or organization. (Von Bertalanffy, GST, pp. 148-9)


MORPHOLOGY   The study of structure or form and the features comprised in the form and structure of an organism or any of its parts, in which a definite behavioral approach is employed and a specific methodology is used. (John Warfield)

MORPHOSTASIS   the process in complex system-environment exchanges that tends to serve or maintain a system's given form, organization, or state. Examples are homeostatic processes in organisms, and ritual in socio-cultural systems.

MULTIFINALITY   a condition in which similar initial conditions lead to different end effects.

  within a multistable system, subsystem adapts to subsystem in exactly the same way as an animal adapts to its environment.

  1. The environment is assumed to consist of large numbers of subsystems that have many states of equilibrium. The environment is thus assumed to be polystable.
  2. Whether because the primary joins between the subsystems are few, or because equilibria in the subsystem are common, the interaction between subsystems is assumed to be weak.
  3. The organism coupled to this environment will adapt by the basic method of ultrastability, i.e., by providing second-order feedbacks that veto all states of equilibrium except those that leave each essential variable within its proper limits.
  4. The organism's reacting part is itself divided into subsystems between which there is no direct connection. Each subsystem is assumed to have its own essential variables and second order feedback. To trace the behavior of the multistable system, suppose that we are observing two of the subsystems, e.g., A and B and that their main variables are directly linked so that changes of either immediately affect the other, and that for some reason all the other subsystems are inactive. The first point to notice is that, as the other subsystems are inactive, their presence may be ignored; for they become like the 'background'. Even some are active, they can still be ignored if the two observed subsystems are separated from them by a wall of inactive subsystems. The next point to notice is that the two subsystems, regarded as a unit, form a whole which is ultrastable. This whole will therefore proceed, through the usual series of events, to a terminal pattern of behavior. If, however, we regard the same series of events as occurring, not within one ultrastable whole, but as interactions between a minor environment and a minor organism, each of two subsystems, then we shall observe behaviors homologous with those observed when interaction occurs between 'organism' and 'environment'. Trial and error will appear to be used; and, when the process is completed, the activities of the two parts will show co-ordination to the common end of maintaining the essential variables of the double system within their proper limits. Exactly the same principle governs the interactions between three subsystems. If the three are in continuous interaction, they form a single ultrastable system which will have the usual properties. As illustration, we can take the interesting case in which two of them, A and C say, while having no immediate connection with each other, are joined to an intervening system B, intermittently but not simultaneously. Suppose B interacts first with A: by their ultrastability they will arrive at a terminal pattern of behavior. Next B and C interact. If B's step-mechanisms, together with those of C, give a stable pattern of behavior to the main variables of B and C, then that set of B's step-mechanism values will persist indefinitely; for when B rejoins A the original stable pattern of behavior will be re-formed. But if B's set with C's does not give stability, then it will be changed to another set. It follows that B's step-mechanisms will stop changing when, and only when, they have a set of values which forms fields stable with both A and C. (Ashby, l960, pp. 208-2l0)

NECESSITY   refers to the urgency with which one wishes to establish a relation or connection found missing. (H. Brun)

NEED   a condition which must be met continuously and unconditionally if living organisms are to be able to be motivated to maintain themselves, their identities, their existence. Continuously: because the conditions continue in consequence of having been met. Unconditionally: because without the conditions called "needs" having been met no other condition exists. (H. Brun)

  An interval scale measurement of the difference between the measure of performance and the resources expended to obtain the level of performance. (Turoff)

NOISE   refers not simply to audible sound but rather to any undesired information in a communication channel which is not part of the intended message. Thus, smudges on a printed page, static on a radio, "ghosts" on a television can be interpreted as noise according to this definition. Because noise is an evaluative term, it occurs only in the receiver. The channel does not know the difference. (Umpleby)

NORMATIVE   relating to an authoritative standard or principle of right action binding on the members of a group and serving to guide, control, or regulate proper and acceptable behavior; a pattern or trait taken to be typical in the behavior of a social group. (Umpleby)

OBJECTIVE   An objective is something that a DECISION MAKER seeks to accomplish or to obtain by means of his decision. A decision maker may have more than one objective (the MULTIPLE-OBJECTIVES case).

An objective may be specified in a more or less general Fashion, may be quantified or not quantified, and is usually part of a HIERARCHY OF OBJECTIVES. The term GOAL is sometimes used to denote a very general objective( at the top of the hierarchy) and TARGET is used to mean a very definite objective. Example: "The goal of allocating money to the municipality was to increase the quality of urban life. The immediate objectives were to improve public transportation and fire services. A 10% reduction of average travel time from home to work and a 70% decrease of average alarm-to-action time taken by the fire brigades were set forth as targets."

The multiple objectives of a single decision maker are usually COMPETITIVE: i.e. the improvement in one of them is associated with a deterioration in another (usually because of limited resources or because of other CONSTRAINTS). Competitive objectives are sometimes referred to as CONFLICTING OBJECTIVES. However, one should speak about a conflict and about conflicting objectives only if there are two or more decision makers who have different objectives and who act on the same system or share the same resources. In the example given above, the director of urban transportation and the director of city fire services have conflicting objectives. At the same time, the mayor of the city, if he were the single decision maker, would look at these objectives as competitive. If the two directors are left without a coordinating influence by the mayor (who would, for example, decide how to allocate the resources), a CONFLICT SITUATION may result. (See GAME THEORY.) With the mayor's interventions, the system becomes a hierarchy of decision makers, and the conflict may be resolved. When the extent to which an objective is attained is measurable on some appropriate scale, one can speak about the degree of attainment of the objective. In SYSTEMS ANALYSIS, one often uses [PROXY OBJECTIVES:] objectives other the original ones, but such that are measurable and can be quantitatively discussed. A proxy objective should at least point in the same direction as the original one; for example, "reduction of mean travel time" in urban transportation is a proxy for "improved services." In a mathematical description, the measures of the multiple objectives Q1, Q2, ...Qn are considered to be coordinates of a point in the n-dimensional OBJECTIVE SPACE. Then, the TARGET VALUES Tl, T2,..Tn prescribed for the n objectives are considered to be coordinates of the TARGET POINT in this space. When the target value requirements are set forth as some intervals rather than single Numbers, they define a region in the objective space that is referred to as a TARGET SET. (IIASA)

OBJECTIVITY   old definition: an observation is considered objective if the characteristics of the observer do not appear in the observation. New definition: shared objectivity (Heinz Von Foerster, l970)

  1. One who watches without participating.
  2. The source of factual evidence; a person who communicates his sense impression of the external environment.
  3. Everything said is said to an observer. (Witz, in Von Foerster, 1974)
  4. Observer dependence - the concept that knowledge of reality is dependent upon the perceptions of the observer.
  5. Observer inseparability - the concept that observation or measurement affects the state of the object being observed, that is, objective measurement or observation from outside a system is not possible, and the act of observing makes the observer part of the system under study. Therefore, the observer or measuring device should be included in the definition of the system. (Weinberg)
  6. A system which, through recursive interactions with its own linguistic states, may always linguistically interact with its own states as if with representations of its interactions. (Maturana and Varela, 1979)

OCCAM'S RAZOR   named after William of Occam. Given a choice between two explanations, choose the simplest -- the explanation which requires the fewest assumptions.

ONTOGENY   the history of the structural transformations of a unity. (Maturana and Varela, 1979)

OPEN SYSTEM   an entity with a boundary that is not closed. It receives inputs and produces outputs. (Umpleby)

ORGANIZATION   the relations that define a system as a unity, and determine the dynamics of interaction and transformations which it may undergo as such a unity, constitute the organization of a system. (Maturana and Varela, 1979)

OPERATIONALIZATION   the specification of measurable empirical referents for abstract definitions, concepts, and hypotheses. (Young, p. l09)

OPERATIONS RESEARCH   Operations research (operational research in Britain) as understood today is essentially identical to SYSTEMS ANALYSIS. Historically, it was a narrower area of activity that stressed quantitative methods and did not concern itself with TRADEOFFS between OBJECTIVES and means or with problems of equity. It was defined by the Operational Research Society of Great Britain as follows (OPERATIONAL RESEARCH QUARTERLY, l3(3): 282, l962): Operational research is the attack of modern science on complex problems arising in the direction and management of large systems of men, machines, materials and money in industry, business, government and defense. Its distinctive approach is to develop a scientific model of the system, incorporating measurements of factors such as change and risk, with which to predict and compare the outcomes of alternative decisions, strategies or controls. The purpose is to help management determine its policy and actions scientifically. (IIASA)

OPPORTUNITY COST   Opportunity cost is defined as the advantage forgone as the result of the acceptance of an ALTERNATIVE. It is measured as the BENEFITS that would result from the next best alternative use of the same resources that were rejected in favor of the one accepted. Opportunity cost is difficult, perhaps impossible, to measure precisely. (IIASA)

OPTIMIZATION   Optimization is an activity that aims at finding the best (i.e., optimal) solution to a problem. For optimization to be meaningful there must be an OBJECTIVE FUNCTION (see below) to be optimized and there must exist more than one FEASIBLE SOLUTION, i.e., a solution which does not violate the CONSTRAINTS. The term optimization does not apply, usually , when the number of solutions permits the best to be chosen by inspection, using an appropriate CRITERION (see DECISION THEORY). One distinguishes SINGLE OBJECTIVE and MULTIOBJECTIVE OPTIMIZATION. In the first case, the objective is SCALAR-VALUED (it can be measured by a single number); in the second, the objective is VECTOR-VALUED (its value is expressed by an n-tuple of numbers). In mathematical terms, the formulation of an optimization problem involves DECISION VARIABLES, Xl, X2,..Xn, the OBJECTIVE FUNCTION,

Q = f(Xl,X2,...Xn)

constraint relations, usually of the form

Gi(Xl,X2,.....Xn) greater than or equal to O, i = l,2,.....m.

The OPTIMAL SOLUTION (or "solution to the optimization problem") is values of decision variables xl, x2,...xn that satisfy the constraints and for which the objective function attains a maximum (or a minimum, in a minimization problem). Very few optimization problems can be solved analytically, that is, by means of explicit formulae. In most practical cases appropriate computational techniques of optimization (numerical procedures of optimization) must be used. Among those techniques LINEAR PROGRAMMING permits the solution of problems in which the objective function and all constraint relations are linear. NONLINEAR PROGRAMMING does not have this restriction, but can manage many fewer decision variables and constraints. INTEGER PROGRAMMING serves to solve problems where the decision variables can take only integer values. STOCHASTIC or PROBABILISTIC PROGRAMMING must be used for problems where the objective function or constraint relations contain random-valued parameters (in the latter case, the problem is referred to as a CHANGE-CONSTRAINED PROBLEM). A special case is dynamic optimization problems where the decision variables are not real numbers or integers but functions of one or more independent variables -- functions of time or space coordinates, for example. Dynamic optimization problems are sometimes referred to as "optimal control problems." There exist special techniques to solve such problems; they often make use of DISCRETIZATION of the independent variables, for example dividing the time axis into a number of intervals and considering the solutions to be constant over those intervals. A single-objective optimization problem may have (and usually does have) a single-valued, unique solution. The solution to a multiobjective problem is, as a rule, not a particular value, but a set of values of decision variables such that, for each element in this set, none of the objective functions can be further increased without a decrease of some of the remaining object functions (every such value of a decision variable is referred to as PARETO-OPTIMAL). (IIASA)

OUTPUT   any change produced in the surrounding by a system. (Umpleby)

  1. an outstandingly clear or typical example or archetype. (Webster's)
  2. The total pattern of perceiving, conceptualizing, acting, validating, and valuing associated with a particular image of reality that prevails in a science or a branch of science. (Kuhn)
  3. A theoretical model to explain a type of social behavior. (Dict. of Anthropology)

PARADOX   a tenet contrary to received opinion; a statement that is seemingly contradictory or opposed to common sense and yet perhaps is true; a self- contradictory statement that at first seems true; an argument that apparently derives self-contradictory conclusions by valid deduction from acceptable premises. (Webster's) A paradox is not the same as a contradiction. "The shirt is blue; the shirt is not blue," and "It is raining; it is not raining," are examples of contradictions. A paradox occurs when one makes an assumption and, following a logical argument, arrives at the converse. A paradox will always result when one formulates a set that contains itself. Below are several examples:

  1. Suppose there is a small town that consists only of men. There are two kinds of men in this town--those who shave themselves and those who are shaved by the barber. Who shaves the barber? If he shaves himself, then he is shaved by the barber. But if he is shaved by the barber, then he shaves himself. If the barber is assumed to be in one set, he appears in the other. This situation occurs because the barber both appears in the set and is used to define the set.
  2. A person from the island of Crete asserts, "All Cretans are liars." We can conclude that if he is telling the truth, then he is lying. But if he is lying, then he is telling the truth. Once again an element of the set is referring to the set.
  3. Consider a businessman accused of accepting a bribe. He claims, "I did not take the bribe." There are two possible interpretations of this statement. Either he is a knowledgeable observer making a correct statement, or he is a knowledgeable observer lying to avoid going to jail. The businessman is both the observer and the person being observed. We have no way of knowing which role he is playing.

As the third example indicates, paradox leads to "undecidability". When two equally correct interpretations are possible, in the absence of further information, no decision other than a random choice is possible. (Umpleby)

  1. that which determines the structure of a system. Parameters themselves can be changed by inputs, but usually the parameters determine how input will be transformed into outputs. In the linear equation y = ax + b, the slope "a" and the y-intercept "b" are the parameters; "x" is the independent variable and "y" the dependent variable. (Umpleby)
  2. In computer science PARAMETER is an entry in a command or routine that must be replaced with specific data prior to execution. (Arbib)
  3. In a system theory PARAMETERS are used to distinguish between systems that are described by similar sets of equations--the choice of parameters fits the model to a specific situation. (Arbib)

The New York Times Magazine of May l3, l979, discusses definitions of parameter". The shortest one that seems neat: PARAMETER - that what gives definition. another one: PARAMETER -a constant whose value may vary. limit combining both: PARAMETER - a variable that gives definition to a system.

  the "best that could be achieved without disadvantaging at least one group." (Allan Schick, in Louis C. Gawthrop, l970, p.32)

PECEPTRON   a machine that determines whether or not an event fits a certain pattern; a machine that makes decisions by adding up evidence obtained from many small experiments. (Minsky and Papert, p. 4)

PERFECT INFORMATION   a characteristic of a situation in which all data relevant to a problem is known. Numbers are available for all variables necessary for a solution, through some of the numbers may be the result of estimates rather than measurements. "Perfect" in this context refers to completeness with no implied judgment about quality. (Umpleby)

PHASE PLANE   If a process can be described by two key variables, then the relationship may be plotted 2 dimensionally - in the phase plane. (Arbib)

  defined by the properties of the unity or unities that constitute it, either singly or collectively through their transformations or interactions. Thus whenever a unity is defined or a class of unities is established which can undergo transformations or interactions, a phenomenological domain is defined. (Maturana and Varela, 1979)

  1. the study of all possible appearances in human experience, during which considerations of objective reality and of purely subjective response are temporarily left out of account.
  2. a philosophical movement based on phenomenology, originated by Edmund Husserl about 1905.

PHYSICAL SPACE   the space within which the phenomenology of autopoiesis of living systems takes place. (Maturana and Varela, 1979)

PLANNING   The process of generating and comparing different courses of action and then choosing one prior to action. It takes the system from a high-level specification of what is to be done to a detailed specification of how to do it. (Arbib)

POLYSTABLE SYSTEM   a state-determined system that has partial, fluctuating, and temporary independencies within the whole. Its parts have a high proportion of equilibrial states. A polystable system can be richly joined, so that almost every variable is joined to almost every other, or it can be poorly joined. A polystable system midway between the two will show a somewhat confused picture. Subsystems will be formed with kaleidoscopic variety and will persist only for short times; some will be stable for a brief interval, only to be changed and to disintegrate. The number of stable variables will tend to climb as a few subsystems become stable, only to fall back by a larger or smaller amount as they become unstable. The oscillations will be large until all subsystems become stable at the same time. Then the system as a whole will remain stable. (Ashby, 1960, Chapter l3)

  1. power resides where information resides (McCulloch, see the PRINCIPLE OF REDUNDANCY OF POTENTIAL COMMAND;
  2. power is the ability to limit choice. (Von Foerster in the mid 1960's), A does not have power over B unless A is able to constrain a necessary transaction of B;
  3. a power relationship requires compliance (Maturana);
  4. power is the consequence, submission is the cause (von Foerster, 1983).
  5. Indirect or secondary exercise of power occurs when A constrains the necessary transactions of C so C will constrain the necessary transactions of B. A secondary boycott is an example.
  6. Power distorts information. Hence, the President, who needs to be well informed, is often poorly informed because his power distorts the information given to him. No adviser wants to be the bearer of bad news or news which the President is thought not to want to hear. Deliberate steps are required to achieve accurate information.
  7. If one accepts the idea that one is powerless, then one feels justified in threatening those one defines as powerful. However, the "powerful" usually feel threatened by the "powerless" who invariably outnumber them. Threats by the powerless against the powerful can make the powerful feel that repression is necessary in order to preserve the safety of themselves and their families.

PREDICTION   "to predict the future is to perform an operation on the past," Norbert Wiener. "The essential point is that the agent in the act of prediction depends wholly on the actual past and not in the least on the actual future." (Ashby, "Induction, Prediction, and Decision-Making in Cybernetic Systems")

PRINCIPLE OF COMPARATIVE ADVANTAGE   units of production -- whether people or machines -- will be employed in those processes in which they are relatively more productive. This is the standard rebuttal for those who fear that machines will replace people. The principle implies that both people and machines can be fully employed regardless of their relative productivity. The long-run impact of industrialization and automation, it is argued, is not to reduce the size of the labor force but rather is to use machines in tasks best performed by machines and to use people in tasks which can only be done by people. (H. Simon, 1965, p. 6)

PRINCIPLE OF COMPLEMENTARITY   Some observations can never be made simultaneously. For example, one cannot see an electron as a particle and a wave at the same time. Two different experimental situations are necessary, and they cannot be realized simultaneously. The principle was first formulated by Niels Bohr. (Lefebvre, 1983, p. xxv)

PRINCIPLE OF ECONOMIES OF SCALE   large-scale organizations enjoy numerous competitive advantages, such as the ability to buy in bulk quantities, thereby reducing per-unit costs. (Umpleby)

PRINCIPLE OF EVENTS OF LOW PROBABILITY   the fundamental purpose of a system should not be jeopardized, nor its fundamental objectives significantly compromised, in order to accommodate events of extremely low probability. (R. Machol, 1965, pp. l-7)

PRINCIPLE OF THE HUMBLE ELITE   For certain governmental functions, shining of the function must be handled by experts. Such an elite must be humble in that it accepts the responsibility to explain its decisions to the public and be responsive to their viewpoints. (Arbib)

PRINCIPLE OF LEAST EFFORT   a system will try to adapt to its environment or will try to change the environment to suit its needs, whichever is easier. (Umpleby)

PRINCIPLE OF MAXIMAL AUTONOMY   The purpose of a planning network is to provide tools for local planning, rather than primarily to provide centralized control of the planning at different nodes (Arbib)

  a criterion for deciding among scientific theories or explanations. One should always choose the simplest explanation of a phenomenon, the one that requires the fewest leaps of logic. (Umpleby)

PRINCIPLE OF REDUNDANCY OF POTENTIAL COMMAND   power resides where information resides. (Warren McCulloch)

  "every isolated, determinant dynamic system obeying unchanging laws will develop organisms that are adapted to their environments." "The argument is simple enough in principle. We start with the fact that systems in general go to equilibrium. Now most of a system's states are non-equilibrial

So in going from any state to one of the equilibria, the system is going from a larger number of states to a smaller. In this way, it is performing a selection, in the purely objective sense that it rejects some states, by leaving them, and retains some other state, by sticking to it. Thus, as every determinate system goes to equilibrium, so does it select. We have heard ad nauseam the dictum that a machine cannot select; the truth is just the opposite; every machine, as it goes to equilibrium, performs the corresponding act of selection." (Ashby in W. Buckley (ed.) MODERN SYSTEMS RESEARCH FOR THE BEHAVIORAL SCIENTIST, P.115)

"A system shows self-organization, if its behavior shows increasing redundancy with increasing length of the protocol. Since redundancy may increase either by a reduction of H or an increase in H max, and since H max may be increased only by a redefinition of the system (a change in the number of its states), we may speak of the organization of a system only in the case where the increase in redundancy results from a decrease in H. (Ashby, Handout, 1961) See also SELF-ORGANIZING.

PRINCIPLE OF SUBOPTIMIZATION   Optimizing each subsystem independently will not in general lead to a system optimum, or more strongly, improvement of a particular subsystem may actually worsen the overall system. The principle of suboptimization provides the basis for a link between organizational structure and the policies adopted. (Machol, 1965, pp. l-8) See also SUBOPTIMIZATION.

PRINCIPLE OF SUBOPTIMIZATION   The well-being of an element is dependent on the well-being of the system of which it is a part. It is sometimes necessary for an element to limit its goals and actions in order to preserve the well-being of the system. In acting to achieve its goals one element may come to constrain the actions of another element to the point of serious injury to the other element.

PRINCIPLE OF SUBSIDIARITY   problems are best solved in the subsystem where they arise. This is similar to the idea of management by exception. Subsystems are encouraged to resolve their conflicts themselves without referring them to higher authority. Whatever solution is adopted, the subsystem will have to carry it out. Since their consent is essential, the optimum condition is for them to resolve their conflicts independently. If a solution is worked out by the subsystem, appeal to authority is not necessary. (Wheeler, 1970, p. l33)

PRINCIPLE OF SUPERPOSITION   if input A produces output B and input C produces output D, the principle of superposition holds if input A+C produces output B+D. Otherwise it does not hold. If the principle of superposition applies, the system is linear. The superposition principle is the basis for treating all problems in wave mechanics including interference and diffraction. It is also fundamental for the analysis of electronic circuits. (Umpleby)

PRINCIPLE OF UNDIFFERENTIATED ENCODING   the brain does not perceive light, sound, heat, touch, taste or smell. It receives only neuronal impulses from sensory organs. Thus the brain does not "see light," "hear sounds," etc.; it can perceive only "this much stimulation at this point on my body." The practical consequence is that all perceptions, let alone "thoughts," are deductions from sensory stimuli. They cannot be otherwise. All observations are therefore partly the function of the observer. This situation renders complete objectivity impossible in principle. (Heinz Von Foerster, "On Constructing a Reality.")

PROGRAM   A structure of instructions that spells out step-by-step how a job is to be done by a computer. (Arbib)

PURPOSE   the possession of an internal project or program represented and realized through the components of a unity. (Maturana and Varela, 1979)

RECURSION   Defining a program in such a way that it may call itself, so that use of the program may occur again and again during its execution. (Arbib)

RECURSION   of, pertaining to, or designating: a) a mathematical expression, such as a polynomial, each term of which is determined by application of a formula to preceding terms. b) a formula that generates the successive terms of such an expression. From the Latin "a return."

RECURSIVE SYSTEM THEORY   In a recursive organizational structure any viable system contains, and is contained in a viable system. (Beer, l977)

REDUCTIONISM   a doctrine that maintains that all objects and events, their properties, and our experience and knowledge of them are made up of ultimate elements, indivisible parts. (Ackoff, l974, p. 8)

REDUNDANCY   one minus the ratio of the actual uncertainty to the maximum uncertainty. "This is the fraction of the structure of the message which is determined not by the choice of the sender, but rather by the accepted statistical rules governing the choice of the symbols in question." (Shannon and Weaver, 1948, p. l3)

  1. if an environmental variable (such as temperature) or an input or output variable (such as the flow demand on a system) changes and the system can nearly compensate for those changes in some other variable (such as outlet pressure) then the system is said to be regulated or regulated for that variable. If the regulation is obtained by a static compensation in which some linkage or component is introduced that diminishes the sensitivity to change, then this is static regulation (e.g., a spring scale is designed with materials that thermally compensate the spring against temperature change; a dc motor is designed by the choice of its field windings to give a speed regulation against changes in the load put on the motor; a chemical buffer shifts the operating point of chemical equilibrium to hold the pH of a solution constant). In dynamic regulation, two different switch states (an "on" and an "off" state) are arranged so that the system switches from one state to the other when the regulated parameter rises to an upper limit (an on-off thermostat). In feedback regulation (or control as it is technically referred to), an error signal is produced between the existing state of a system and the desired regulated level. This error signal is operationally acted upon, amplified in power, and fed to an actuator to operate a network which can influence the regulated variable so as to reduce the error, e.g., in biology the Na+ angiotension system. The signal is the sodium concentration. When this concentration decreases, aldosterone is liberated from the adrenal cortex. This agent acts on the kidney distal cubules to increase the reabsorption of sodium ions and re-establish the proper concentration of sodium. (Iberall)
  2. a notion valid in the domain of description of heteropoiesis, that reflects the simultaneous observation and description made by the designer (or its equivalent) of interdependent transitions of the system that occur in a specified order and at specified speeds. (Maturana and Varela, 1979)

REGULATOR   a system which determines (selects) and enforces (maintains) the operating parameters of another system. The regulator may or may not be a subsystem of the system being regulated. (Umpleby)

REGULATOR   something that blocks the flow of variety from disturbances to essential variables. If an automatic pilot is a good regulator, the passengers will have a smooth flight whatever the gustiness outside. They will, in short, be prevented from knowing whether or not it is gusty outside. Thus a good pilot acts as a barrier against the transmission of information. The same argument applies to an air-conditioner. If I live in an air-conditioned room, and can tell, by the hotness of the room, that it is getting hot outside, then that conditioner is failing as a regulator. If it is really good, and the blinds are drawn, I shall be unable to form any idea of what the outside weather is like. The good conditioner blocks the flow inwards of information about the weather. The same thesis applies to the higher regulations achieved by such activities as hunting for food and earning one's daily bread. Thus while the unskilled hunter or earner, in difficult times, will starve and will force his liver and tissues (the essential variables) to extreme and perhaps unphysiological states, the skilled hunter or earner will go through the same difficult times with his liver and tissues never taken to extremes. In other words, his skill as a regulator is shown by the fact, among others, that it prevents information about the times reaching the essential variables. In the same way, the skilled provider for a family may go through difficult times without his family realizing that anything unusual has happened. (Ashby, l956, pp. 200-20l)

REIFICATION   treatment of an analytic or abstract relationship as though it were a concrete entity. (Young, p. l09)

RELATIONS OF CONSTITUTION   determine that the components produced constitute the topology in which the autopoiesis is realized. (Maturana and Varela, 1979)

RELATIONS OF ORDER   determine that the concatenation of the components in the relations of constitution, specification and order be the ones specified by the autopoiesis. (Maturana and Varela, 1979)

RELATIONS OF SPECIFICITY   determine that the components produced be the specific ones defined by their participation in the autopoiesis. (Maturana and Varela, 1979)

REPRODUCTION   any of the processes of replication, copying or self-production. (Maturana and Varela, 1979)

  1. The measure of a system's ability to remain within a domain of stability in response to fluctuations of the system by a disturbance, and the ability of the system to return to that stable domain having once left. (Holling)
  2. The ability of a system to make a smooth transition to a new stable state in response to changes in external conditions. The wider the range of external fluctuations in which the system can obtain a stable state, the greater is the resiliency of the system. (Turoff) See also STABILITY.
  3. a measure of the ability of a system to absorb changes and still persist. (Holling)

RESOURCE ANALYSIS   The process of determining the economic resource IMPACTS of alternative proposals for future COURSES OF ACTION. While in resource analysis, physical quantities are often ultimately translated into monetary terms, the real aim is to measure the probable "resource drain" on the economy that would result from various possible actions. The resource analyst must not only give attention to economic costs but also has to determine if it is feasible to obtain needed physical material and manpower in the required time period. (IIASA)

  1. In DECISION THEORY and in statistics, risk means UNCERTAINTY for which the probability distribution is known. Accordingly, [RISK ANALYSIS] means a study to determine the outcomes of decisions along with their probabilities -- for example, answering the question: "What is the likelihood of achieving a l,000,000 schilling profit in this ALTERNATIVE?" In SYSTEMS ANALYSIS, a DECISION MAKER is often concerned with the probability that a project (the chosen alternative) cannot be carried out with the time and money available. This risk of failure may differ from alternative to alternative and should be estimated as part of the analysis.
  2. In another usage, risk means an uncertain and strongly adverse IMPACT, as in "the risks of nuclear power plants to the population are..." In that case, risk analysis or RISK ASSESSMENT] is a study composed of two parts, the first dealing with the identification of the strongly adverse impacts, and the second with determination of their respective probabilities. (IIASA)

ROLE-PLAYING   A type of SIMULATION in which persons (referred to as actors or players), sometimes with the aid of computers, act out roles as parts of the system being analyzed. For example, experts in different fields may be called upon to simulate the behavior (to predict the response) of specific segments of a regional or national economy being studied. A role-playing simulation in which the actors (players) act out roles as DECISION MAKERS is called GAMING. In gaming, the players usually have different and conflicting OBJECTIVES (in business gaming and war gaming, for example). The players may act as individuals or may be combined into coalitions, or opposing teams. (IIASA)

SAFE FAIL   a property of a system which can recover from failure.

SATISFICING   Satisficing is an alternative to OPTIMIZATION for cases where there are MULTIPLE and COMPETITIVE OBJECTIVES in which one gives up the idea of obtaining a "best" solution. In this approach one sets lower bounds for the various objectives that, if attained, will be "good enough" and then seeks a solution that will exceed these bounds. The satisficer's philosophy is that in real-world problems there are too many uncertainties and conflicts in values for there to be any hope of obtaining a true optimization and that it is far more sensible to set out to do "well enough" (but better than has been done previously). (IIASA)

SCENARIO   A scenario is an outline of an hypothesized chain of events. The term is used to denote:

  1. a FORECAST based on loose assumptions rather than on a more formal inference from the past or
  2. a synopsis of a proposed COURSE OF ACTION. (IIASA)
  3. a sequence of possible events to be studied in a system of interest. (Arbib)

SCHEMA   A person's point of view on some set of issues which greatly determines the way he or she responds to them. (Arbib)

SCIENTIFIC METHOD   a sequence of procedures intended to produce agreement among a set of observers, for example:

  1. Define a problem,
  2. Gather pertinent data,
  3. Form a working hypothesis or explanation,
  4. Do experiments to test the hypothesis,
  5. Interpret the results,
  6. Draw a conclusion and modify the hypothesis as needed.

SECOND LAW OF THERMODYNAMICS   elements in a closed system tend to seek their most probable distribution; in a closed system entropy always increases. The paraphrases below were compiled by Heinz Von Foerster.

  1. Clausius (l822-l888) It is impossible that, at the end of a cycle of changes, heat has been transferred from a colder to a hotter body without at the same time converting a certain amount of work into heat.
  2. Lord Kelvin (l824-l907) In a cycle of processes, it is impossible to transfer heat from a heat reservoir and convert it all into work, without at the same time transferring a certain amount of heat from a hotter to a colder body.
  3. Ludwig Boltzmann (l844-l906) For an adiabatically enclosed system, the entropy can never decrease. Therefore, a high level of organization is very improbable.
  4. Max Plank (l858-l947) A perpetual motion machine of the second kind is impossible.
  5. Caratheodory (l885-l955) Arbitrarily near to any given state there exist states which cannot be reached by means of adiabatic processes.

(From Sears and Zemansky): 100% conversion of heat into mechanical work is not possible by any form of engine. (p. 342) There is a tendency in nature to proceed toward a state of greater molecular disorder. This one-sidedness of nature produces irreversible processes. (p. 347)

SECONDARY DECISION   Secondary decisions are those choices made by the analyst that determine the way in which SYSTEMS ANALYSIS of a given problem or issue will be performed. They include making the simplifying assumptions by which a complex issue will be made tractable in analysis, choosing the forms of MODELS, selecting the techniques of computation and SIMULATION, deciding what data have to be acquired, judging what support by experts of various disciplines to use in performing the analysis, and so on.

The secondary decisions are distinguished from PRIMARY DECISIONS, that is, the decisions to be taken by the DECISION MAKER and related to the object problem or issue to which a systems analysis is applied. (IIASA)

SELECTION   a process of differential realization of a production of unities in a context that specifies the unitary organization that can be realized. In a population of autopoietic unities, selection is a process of differential realization of autopoiesis, and hence, of differential self-production. (Maturana and Varela, 1979)

  the domain of self-observation. (Maturana and Varela, 1979)

  St Thomas Aquinas was probably the most influential Christian thinker. He constructed logical proofs of the existence of God. One of these proofs referred to God as the ultimate organizer or designer. The argument was that everything had to be organized and this called for an organizer. In turn, the organizer had to be organized and so on back the original organizer who had to have existed from eternity: this was God. If something is organized we tend to feel that an outside influence must have organized it at some time. But it need not be so. The concept of a self-organizing system is important because it now seems that life itself came about through a self-organizing process whereby different chemicals came together in a more or less chance fashion and gradually organized themselves into living patterns. Of course, it may still be argued that there was a need for God to organize the chemicals in such a way that they could become self-organizing.

A chain made out of paper clips suggests that someone has taken the trouble to link paper clips together to make a chain. It is not in the nature of paper clips to make themselves up into a chain. But, if you take a number of paper clips, open them up slightly and then shake them all together in a cocktail shaker, you will find at the end that the clips have organized themselves into short or long chains. The chains are not so neat as chains put together by hand but, nevertheless, they are chains. A teacher can organize her class into groups by assigning each child to a specific group and picking the group leaders. She could also tell the children to organize themselves into groups of five and then let them get on with it in a self-organizing fashion. The diagram shows an object that has a magnet out on a prong (bottom of a Y) and two metal plates on the bulb (top of a Y). If we shake up a number of these objects we find that they tend to organize themselves into the arrangement shown. Once the magnet comes into contact with the metal plate it tends to stick there. In other words once something has happened, it does not un-happen so easily. It is this asymmetry that is the basis of self-organization. In the way our mind deals with the outside world in terms of perception we can find a self-organizing system. (De Bono) See also PRINCIPLE OF SELF-ORGANIZATION.

     Y Y
        Y Y
         Y Y


  The concept of a self-organizing system has changed over time. In the early days it was defined as a system which changes its basic structure as a function of its experience and environment. The term appears to have been used first by Farley and Clark of Lincoln Laboratory in l954 in their paper in the Transactions of the Institute of Radio Engineers, Professional Group on Information Theory. (Marshall C. Yovits, 1962, Preface) However, it is important to note that an organism does not organize itself independent of its environment. Von Foerster persuasively argued that only organisms and their environments taken together organize themselves. (Von Foerster, 1960). Ashby redefined a self-organizing system to be not an organism that changes its structure as a function of its experience and environment but rather the system consisting of the organism and environment taken together. (Ashby, 1960)

  when a unity produces another with a similar organization to its own, through a process that is coupled to the process of its own specifications. Only autopoietic systems can self-reproduce. (Maturana and Varela, 1979)

SENSITIVITY ANALYSIS   A procedure to determine the sensitivity of the outcomes of an ALTERNATIVE to changes in its parameters (as opposed to changes in the ENVIRONMENT; see CONTINGENCY ANALYSIS, A FORTIORI ANALYSIS). If a small change in a parameter results in relatively large changes in the outcomes, the outcomes are said to be sensitive to that parameter. This may mean that the parameter has to be determined very accurately or that the alternative has to be redesigned for low sensitivity. (IIASA)

SHANNON'S TENTH THEOREM   "If the correction channel has a capability equal to Hy(x) (the amount of additional information that must be supplied per second at the receiving point to correct the received message), it is possible to so encode the correction data as to send it over this channel and correct all but an arbitrarily small fraction of the errors. This is not possible if the channel capacity is less than Hy(x)." (Shannon and Weaver, 1948, p. 68)

  1. the operation of a dynamic model in order to obtain a sequence of?utcomes that could occur in a real world system. Simulations of social processes can be accomplished either by human player games or by computer programs or by a combination of the two. Rather than simple computing the solution to a set of equations, a simulation produces a synthetic history oh the process. Beginning with a set of initial conditions, the simulation plays through the various kinds of events which might occur.
  2. Simulation is the term applied to the process of modeling the essential features of a situation and then predicting what is likely to happen by operating with the MODEL cace by case--i.e., by estimating the results of proposed actions from a series of imaginary experiments (imaginary because they are performed on the representation of the situation, the model, rather than on the situation itself). Most frequently, the simulation is a [COMPUTER SIMULATION] in which the representation is carried out numerically on a digital computer. It may also be done on an analogue computer or by means of a physical representation, say by a wooden airfoil in a wind tunnel. [MAN-MACHINE SIMULATION] is a simulation that employs a MAN-MACHINE MODEL.


SIZE PRINCIPLE   In n-person, zero-sum games, where side payments are permitted, where players are rational, and where they have perfect information, only minimum winning coalitions occur. In social situations similar to n-person, zero-sum games with side payments, participants create coalitions just as large as they believe will ensure winning and no larger. (Wm. Riker, p. 32)

SPECIALIZATION   In a system consisting of elements with roughly equal and constant CHANNEL CAPACITY (information processing capability), an increase in the channel capacity of the system requires specialization of the tasks performed by each element.

SPECIES   a population or collection of populations of reproductively interconnected individuals which, thus, are nodes in a historical network. (Maturana and Varela, 1979)

STABILITY   the tendency of the variables or components of a system to remain within defined and recognizable limits despite the impact of disturbances. (Young, p. l09)

STABILITY   (expanded or global stability) The ability of a system to persist and to remain qualitatively unchanged in response either to a disturbance or to fluctuations of the system caused by a disturbance. This idea of stability combines the concepts of traditional stability and Holling's new concept of RESILIENCE. (Holling)

STABILITY   The capacity of an object or system to return to equilibrium after having been displaced. Note with two possible kinds of equilibrium one may have a static (linear) stability of rest or a dynamic (nonlinear) stability of an endlessly repeated motion. (Iberall)

STABILITY   a system is stable if, when perturbed, it returns to its original state. The more quickly it returns, the more stable it is.

STATE   The state of a system at a given instant is the set of numerical values which its variables have at that instant. (Ashby, l960, p. l6)

STATE-DETERMINED SYSTEM   a system whose path and/or final state are uniquely determined by the initial state of the system regardless of the way in which the initial state came into being. (Young, p. ll0)

STATE-DETERMINED SYSTEM   a concept that is central to the theory of mechanism. If a set of variables is state-determined, and we elicit its canonical representation by primary operations, then our knowledge of that system is COMPLETE. It is certainly not a complete knowledge of the real "machine" that provides the system, for this is probably inexhaustible; but it IS complete knowledge of the system abstracted--complete in the sense that as our predictions are now single-valued and verified, they have reached (a local) finality. If a tipster names a single horse for each race, and if his horse always win, then though he may be an ignorant man in other respects, we would have to admit that his knowledge in this one respect was complete. Because knowledge of the state-determined system is complete and maximal, all the other branches of the theory of mechanism, which treat of what happens in other cases, must be obtainable from this central case as variations on the question: what if my knowledge is incomplete in the following way...? (Ashby, l960, p. 270)

STATE OF THE WORLD   State of the world in connection with a COURSE OF ACTION means the aggregate of natural, economic, social, cultural, and other conditions on which the presumed CONSEQUENCES must depend and to which the course of action must be matched. A FORECAST of the state of the world is required to predict the results of any course of action. See ENVIRONMENT.(IIASA)

STATES   the raw data of cybernetics; aspects, features, qualities, attributes, properties. classifications; the observables, distinguishables. States may be either unanalyzed or analyzed; if the former, they may be represented by single symbols; if the latter, they may be represented by compound symbols or vectors. For those who demand that a state be a state OF something, we may redefine STATE as any aspect, feature, etc., of a NOMINAL ENTITY, that may change without impairing the identity of the nominal entity. This, in turn, requires that we define a nominal entity as any object of discourse; anything with sufficient coherence and persistence to be treated as an isolate in discourse; anything capable of interpersonal reference; anything graspable by the tongs of language. A system is then seen as a formalization of a nominal entity by the specification of a set of states of the entity. (George W. Zopf, Handout by Ashby, 1961)

STATICAL PHENOMENOLOGY   the phenomenology generated by the relations between properties of components. (Maturana and Varela, 1979)

STOCHASTIC   partially random or uncertain, not continuous; a stochastic variable is neither completely determined nor completely random; in other words, it contains an element of probability. A system containing one or more stochastic variables is probabilistically determined. (Ithiel Pool)

STRUCTURE   the actual relations which hold between the components which integrate a concrete machine in a given space. (Maturana and Varela, 1979)

SUBOPTIMIZATION   Suboptimization refers to the analysis to assist a lower level decision as a step toward the attainment of a higher level objective to which the lower level decision is to contribute. Thus, an OPTIMIZATION of a city's streetcar operations would be a suboptimization if the higher level aim is to optimize the entire public transportation system. Analysts and decision makers must always suboptimize--that is, consider actions that pertain to only part of the elements that enter a problem--neglecting some things and fixing other arbitrarily. Even if all suboptimization problems relevant for a higher level problem are successfully solved, this will not mean, usually, that the higher level problem will be optimized. One could usually do better by treating all partial problems and their interrelationships simultaneously. (IIASA)

  A synergistic system is nonlinear. In a synergistic system, summing previously separate inputs produces an output which is greater than or different from the sum of the separate outputs.

  1. a set of variables selected by an observer. (Ashby, 1960)
  2. Usually three distinctions are made: 1. An observed object. 2. A perception of an observed object. This will be different for different observers. 3. A model or representation of a perceived object. A single observer can construct more than one model or representation of a single object. Some people assume that 1. and 2. are the same. This assumption can lead to difficulties in communication. Usually the term "system" is used to refer to either 1. or 2. "Model" usually refers to 3. Ashby used the terms "machine," "system," and "model" in that order for the three distinctions. (Umpleby)
  3. a set or arrangement of entities so related or connected so as to form a unity or organic whole. (Iberall)
  4. Any definable set of components. (Maturana and Varela, 1979)

SYSTEMS ANALYSIS   This term has many different meanings. In the sense adopted for the Handbook, systems analysis is an explicit formal inquiry carried out to help someone (referred to as the DECISION MAKER) identify a better COURSE OF ACTION and make a better decision than he might otherwise have made. The characteristic attributes of a problem situation where systems analysis is called upon are complexity of the issue and uncertainty of the outcome of any course of action that might reasonably be taken. Systems analysis usually has some combination of the following: identification and re-identification) of OBJECTIVES, CONSTRAINTS, and alternative courses of action; examination of the probable CONSEQUENCES of the alternatives in terms of costs, benefits, and RISKS; presentation of the results in a comparative framework so that the decision maker can make an informed choice from among the alternatives. The typical use of systems analysis is to guide decisions on issues such as national or corporate plans and programs, resource use and protection policies, research and development in technology, regional and urban development, educational systems, and?alth and other social services. Clearly, the nature of these problems requires an interdisciplinary approach. There are several specific kinds or focuses of systems analysis for which different terms are used: A systems analysis related to public decisions is often referred to as a POLICY ANALYSIS (in the United States the terms are used interchangeably). A systems analysis that concentrates on comparison and ranking of alternatives on basis of their known characteristics is referred to as DECISION ANALYSIS.

That part or aspect of systems analysis that concentrates on finding out whether an intended course of action violates any constraints is referred to as FEASIBILITY ANALYSIS. A systems analysis in which the alternatives are ranked in terms of effectiveness for fixed cost or in terms of cost for equal effectiveness is referred to as COST-EFECTIVENESS ANALYSIS. COST- BENEFIT ANALYSIS is a study where for each alternative the time stream of costs and the time stream of benefits (both in monetary units) are discounted (se?DISCOUNT RATE) to yield their present values. The comparison and ranking are made in terms of net benefits (benefits minus cost) or the ratio of benefits to costs. In RISK-BENEFIT ANALYSIS , cost (in monetary units) is assigned to each risk so as to make possible a comparison of the discounted sum of these costs (and of other costs as well) with the discounted sum of benefits that are predicted to result from the decision. The risks considered are usually events whose probability of occurrence is low, but whose adverse consequences would be important (e.g., events such as an earthquake or explosion of a plant). See: OPERATIONS RESEARCH (IIASA)

SYSTEMS ENGINEERING   The systematic application of engineering to solutions of a complete problem in its full environment by systematic assembly and matching of parts in the context of the lifetime use of the system. (Iberall)

TECHNOLOGY   an object or sequence of operations created by man to assist in achieving some goal. A technology is a body of human knowledge that can be passed along from one place to another and from one generation to the next. Examples of technologies are: a bow and arrow; a birth control pill; a nuclear reactor; a legislature; and a planning, programming, budgeting system of accounting.

TELEOLOGY   the philosophical study of manifestations of design or purposes in natural processes or occurrences, under the belief that natural processes are not determined by mechanism but rather by their utility in an overall natural design. Dysteleology is the doctrine of purposelessness in nature. (American Heritage Dictionary) Teleology is associated with vitalism. It explains apparently purposeful animal behavior by saying that the action is performed because it will later be advantageous to the animal. Science, on the other hand, has sought to explain apparently purposeful behavior through the theory of mechanism. The notion that an organism contains a model of the actual world and a model of the desired world and acts so as to make the actual world conform to the desired world is compatible with the theory of mechanism. (Umpleby)

TELEONOMY   the element of apparent purpose or possession of a project in the organization of living systems, without implying any vitalistic connotations. Frequently considered as a necessary if not sufficient defining feature of the living organization. (Maturana and Varela, 1979)

THEORY   An imaginative formulation of apparent relationships or underlying principles of certain observed phenomena. It may have been verified to some extent, or it may be pure hypothesis or conjecture. (Iberall)

TRADE-OFF   Trade-off means an exchange of one quality or thing for another. Thus, in comparing alternative configurations for transport aircraft, it may be possible to trade off speed for payload and still maintain the same total transport capability per month in the system. In VALUE ANALYSIS and DECISION THEORY the concept of tradeoffs in the DECISION MAKER'S preferences is used extensively as a basis for establishing MULTIATTRIBUTE VALUE FUNCTIONS and MULTIATTRIBUTE UTILITY FUNCTIONS. See: VALUE, UTILITY (IIASA)

ULTRASTABILITY   the ability to modify internal relationships and/or to influence environmental conditions in the interests of neutralizing actual or potential obstacles to the maintenance of stability. (Young, p. ll0)

  a term developed by Ashby and defined by him as follows: Two systems of continuous variables (that we called 'environment' and 'reacting part') interact, so that a primary feedback (through complex sensory and motor channels) exists between them. Another feedback, working intermittently and at a much slower order of speed, goes from the environment to certain continuous variables which in their turn affect some step-mechanisms, the effect being that the step-mechanisms change value when and only when these variables pass outside given limits. The step-mechanisms affect the reacting part; by acting as parameters to it, they determine how it shall react to the environment.

We can now appreciate how different an ultrastable system is from a simple system when the conditions allow the difference to show clearly. The difference can best be shown by an example. The automatic pilot is a device which, amongst other actions, keeps the airplane horizontal. It must, therefore, be connected to the ailerons in such a way that when the plane rolls to the right, its output must act on them so as to roll the plane to the left. If properly joined, the whole system is stable and self-correcting: it can now fly safely through turbulent air for, though it will roll frequently, it will always come back to the level. The Homeostat, if joined in this way, would tend to do the same. (Though not well suited, it would, in principle, if given a gyroscope, be able to correct roll.) So far, after a small disturbance; but connect the ailerons in reverse and compare them. The automatic pilot would act, after a small disturbance, to INCREASE the roll and would persist in its wrong action to the very end. The Homeostat, however, would persist in its wrong action only until the increasing deviation made the step-mechanisms start changing. On the occurrence of the first suitable new value, the Homeostat would act to stabilize instead of to overthrow; it would return the plane to the horizontal; and it would then be ordinarily self-correcting for disturbances. There is therefore some justification for the name 'ultrastable'; for if the main variables are assembled so as to make their field unstable, the ultrastable system will change this field till it is stable. The degree of stability shown is therefore of an order higher than that of the system with a single field. (Ashby, l960, pp. 98, l08)

UNCERTAINTY   a measure of variety such that uncertainty (H) is zero when all elements are in the same category. H increases with both the number of categories and their equiprobability. The uncertainty resulting from two or more sets of categories is the sum of the uncertainties of the sets of categories taken independently. H = the sum of P sub i times the log of P sub i, where P sub i is the probability of an element being in the Its category. Since the categories must be specified by an observer, the uncertainty of a system may be different as seen by different observers.

UNCERTAINTY   Because of an unfortunate use of terminology in systems analysis discourse, the word "uncertainty" has both a precise technical meaning and its loose natural meaning of an event or situation that is not certain.

In DECISION THEORY and statistics, a precise distinction is made between a situation of RISK and one of certainty. There is an uncontrollable random event inherent in both of these situations. The distinction is that in a risky situation the uncontrollable random event comes from a known probability distribution, whereas in an uncertain situation the probability distribution is unknown. (IIASA)

UNITY   that which is distinguishable from a background, the sole condition necessary for existence in a given domain. The nature of a unity and the domain in which the unity exists are specified by the process of its distinction and determination; this is so regardless of whether this process is conceptual or physical. (Maturana and Varela, 1979)

  1. In economics, utility means the real or fancied ability of a good or service to satisfy a human want. An associated term is WELFARE FUNCTION (synonym: utility function--not to be confused with UTILITY FUNCTION in DECISION THEORY; see below), which relates the utility derived by an individual or group to the goods and services that it consumes. MARGINAL UTILITY is the change in utility due to a one unit change in the quantity of a good or service consumed.
  2. In DECISION THEORY, utility is a measure of the desirability of CONSEQUENCES of courses of action that applies to decision making under RISK--that IS, under UNCERTAINTY with known probabilities.

The concept of utility applies to both SINGLE-ATTRIBUTE and MULTIATTRIBUTE CONSEQUENCES. The fundamental assumption in UTILITY THEORY is that the DECISION MAKER always chooses the ALTERNATIVE for which the expected value of the utility (EXPECTED UTILITY) is maximum. If that assumption is accepted, utility theory can be used to predict or prescribe the choice that the decision maker will make, or should make, among the available alternatives. For that purpose, a utility has to be assigned to each of the possible (and mutually exclusive) consequences of every alternative. A UTILITY FUNCTION is the rule by which this assignment is done and depends on the preferences of the individual decision maker. In utility theory, the utility measures u of the consequences are assumed to reflect a decision maker's preferences in the following sense: (i) the numerical order of utilities for consequences preserves the decision maker's preference order among the consequences; (ii) the numerical order of expected utilities of alternatives (referred to, in utility theory, as gambles or lotteries) preserves the decision maker's preference order among these alternatives (lotteries). For example if alternative A can have three mutually exclusive consequences, x,y,z, and the decision maker prefers z to y and x to z, the utilities Ul, U2, U3 assigned to x,y,z must be such that U3)U2)U1. If the probabilities of the consequences x,y,z are P1,P2,1-p1,-p2, respectively, the expected utility of alternative A is calculated as

E(u/P) = PlUl + P2U2 + (l-Pl-P2)U3

where P means the probability distribution, characteristic for the alternative (i.P1, P2, 1-P1-P2). (IIASA) If the decision maker prefers alternative B, which has probability distribution Q, to alternative A, the utility assignments in both alternatives must be such that

E(u/Q) 1/2 > E(u/P).

Utility theory provides a basis for the assignment of utilities to consequences by formulating necessary and sufficient conditions to satisfy (i) and (ii). A utility function is defined mathematically as a function u(.) from the set of consequences Y into the real numbers that provides for satisfaction of (i) and (ii). There exist various methods for constructing utility functions. The best-known method is based on indifference judgments of the decision maker about specially constructed alternatives(lotteries). Utility theory permits one to distinguish RISK-PRONE, RISK- NEUTRAL and RISK-AVERSE DECISION MAKERS. For example, if the mutually exclusive payoffs xl,x2,x3 of an alternative A are all expressed in the same units (e.g., schillings), the decision maker is risk-prone if he prefers the alternative A (prefers the lottery) to receiving, with no risk, the expected value of the payoffs (calculated directly as

E(x/P) = plxl + p2x2 + (l-pl-p2)x3).

This preference can also be expressed as

E(u/P) > u(E(x/P))

i.e., the expected utility of the lottery to the risk-prone decision maker is larger than the utility of the expected value of the consequence. The risk-neutral and risk-averse decision makers are defined accordingly. The MULTIATTRIBUTE UTILITY FUNCTION is defined as a function u(.) from the set of multiattribute consequences into the real numbers. This means that it applies to cases where each of the mutually exclusive consequences has several attributes. Multiattribute utility functions, besides having properties (i) and (ii), also express the decision maker's TRADE OFFS among the attributes (compare MULTIATTRIBUTE VALUE FUNCTION). Several special forms of multiattribute utility functions have been developed, including the additive and the multiplicative forms. (IIASA)

VALIDATION   the process of determining how well one system replicates properties of some other system or, more generally, any comparison between the representation of a system and specified criteria. The validation of an operating model cannot be separated from the purpose for which it is designed and used.

VALIDATION   Validation is the process of increasing the confidence that the outputs of the model conform to reality in the required range. In some cases, the model's output can be compared to data from historical sources or from an experiment conducted for?lidation. A model can never be completely validated. We can never prove that its results conform to reality in all respects. It can only be invalidated. Predictive models be validated only by judgment, since a model may fit past data well without having good predictive qualities. (IIASA)

VALUE   Value can be either objective or subjective. In the latter case, it means subjective worth or importance. For example, "the value of future benefits to the DECISION MAKER," "the value of clean air to the society." For the purposes of analysis, the subjective values must be measured on some scale. These measures of value should be based on preferences expressed by the person or group of interest.

In [VALUE ANALYSIS,] one considers that the value v is related to the physical or other objective measure y of a consequence by a subjectively defined [VALUE FUNCTION,] so that v = f(y). A value function usually departs from proportionality, i.e.,it usually is a nonlinear dependence. A typical example is the subjective value of money to an individual: the first l,000 schillings in his savings account are probably of more value to him that the l,000 schillings that would increase the state oh his account from 100,000 to 101,000 schillings. The value of a multiattribute consequence with VALUE-RE?ANT ATTRIBUTES y1,y2,..yn can be expressed by a MULTIATTRIBUTE VALUE FUNCTION, v(yl,y2,..yn). A multiattribute value function must satisfy the following condition:

v(yl,y2,...yn) is greater than or equal to v(y'l,y'2,...y'n)

if and only if the multiattribute consequence (yl,y2,..yn) is preferred or indifferent to (y'1,y'2,...y'n).

Several theories exist according to which a multiattribute value function V(.) can, in appropriate cases, be expressed as an aggregate of single-attribute functions Vi(.). For example, the additive [CONJOINT MEASUREMENT THEORY] assumes that

               v(yl,y2,....,yn) = SUM  Vi(yi).


VARIABLE   a measurable quantity which at every instant has a definite numerical value. If there is any doubt whether a particular quantity may be admitted as a variable, use the criterion whether it can be represented by a pointer on a dial. Pressure, angle, electric potential, volume, velocity, mass, viscosity, population, national income per capita and time itself, to mention only a few, can all be specified numerically and recorded on dials. Eddington's statement on the subject is explicit: "The whole subject matter of exact science consists of pointer readings and similar indications. Whatever quantity we say we are 'observing', the actual procedure nearly always ends in reading the pointer of some kind of indicator on a graduated scale or its equivalent." (Ashby, 1960, p. l5)

  1. in relation to a set of distinguishable elements, either (l) the number of distinct elements, or
  2. the logarithm to the base 2 of that number, the context indicating the sense used. When variety is measured in the logarithmic form, its unit is the "bit," a contraction of "BInary digiT." (Ashby, 1956, P. 126)

VARIETY   the amount of output from a system is limited by the variety possible within the system and/or the variety of input to the system. The number of possible alternative communications between the two systems is limited by that system having the fewest output alternatives and/or the fewest input alternatives. (Charles E. Osgood)

VERIFICATION   A (computer) MODEL is said to be verified if it behaves in the way that the model builder wanted it to behave. This means that the instructions are correct and have been properly programmed. One check for verification is to hold some of the variables constant to determine whether the output changes in anticipated ways as other variables are changed. Another typical check is to test how the model behaves in limit situations. Compare: VALIDATION (IIASA)

VOTING   a formal procedure for assigning authority.


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