Ashby, R. (1956) Introduction to cybernetics. John Wiley: NewYork.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....against a variety of visualizations. Some designers of state based software specification languages have used the term mode as a synonym for state; therefore all states are modes. We instead use the term mode in the engineering sense and as originally defined by Ashby in systems theory [Ash56] Although the visualizations described in the previous section were useful in understanding the MD 11 specification, this anecdotal evidence does not prove their usefulness to a broad class of users and specifications. We are designing experiments with human subjects to validate the application ....

W.R. Ashby, "An Introduction to Cybernetics", John Wiley, 1956.

....in pattern recognition, and of course built his autonomous turtles to study mechanisms underlying the generation of adaptive behaviour [52] W. Ross Ashby formulated theoretical frameworks for understanding adaptive behaviour which are experiencing something of a renaissance in ALife and modern AI [1, 2]. Among many other achievements in a variety of scientific fields, Thomas Gold was a co author of the steady state theory of the universe and founded the Cornell Astrophysics department. Jack Good became a very prominent statistician making important contributions in Bayesian methods. Eliot Slater ....

Ashby, W. R. An Introduction to Cybernetics. Chapman and Hall, 1958.

....firstly, if the various structures of the neural network can be generated and, secondly, if the best of them can be selected by a criterion of their efficiency. The variety or the number of the training neural network states must be adequate in accordance with the general principle of W. Ashby [2]. The complexity of the learned neural network will be optimal if its variety will be adequate under the minimal number of its nodes and their synaptic connections. For known F. Rosenblatt s perceptron consisting of the input (sensor) associative and adjustable layers of the nodes, the ....

Ashby, W.R., An Introduction to Cybernetics. Willey, New York, 1956.

....In the Sections 2, 3 and 4 we will present preliminaries about Kolmogorov complexity and our methodology, in the remaining Sections we will focus on animation models. 2 Systems Science Systems science (or systems theory, or cybernetics) is a fuzzy academic domain and dicult to de ne (see [1]) The research area is characterized by an wide range of applications. One possible de nition is: Systems science is the study and application of general problem solution methods and general principles of control of systems of a large range of types (mechanical, chemical, biological, ....

Ross Ashby. An Introduction to Cybernetics. Chapman and Hall, London, 1957.

....can bee seen as a set of ready to use alternative answers that an organization, as an organism, can give when facing new and unforeseen environmental situations. A similar concept can be derived by the study of complexity, and in particular by the notion of requisite variety in organizations [Ashby, 56] Here an organization is seen as a system that has to manage the trade off between the need of stabilizing its internal processes, and the one of answering to external environmental complexity. An organization is seen as a complexity selector that has mainly the goal to filter between ....

W.R. Ashby, An Introduction to Cybernetics. Part Two: Variety. London, England: Methuen, 1956.

....and shows that it produces a hierarchy of abstract models. Section 4 introduces three variable resolution heuristics. Section 5 shows the results for Kaelbling s 10 10 maze [1] We conclude with some discussion on future research directions. 2 Modelling, Homomorphism and Abstractions Ashby [2] described a model as a state action homomorphism between Markov machines. A homomorphism is a many one mapping that preserves certain operations of interest. For example, the state transition function in a MDP is a good model of the environment if it accurately reflects the probabilistic ....

Ross Ashby. Introduction to Cybernetics. Chapman & Hall, London, 1956.

....it is appropriate to pay tribute to one of the almost forgotten ideas from the dawn of AI. In 1940, the homeostat of W. Ross Ashby (1903 1972) joined the class of systems consisting of particles interacting under constraints. Ashby s Design for a Brain [12] and An Introduction to Cybernetics [13] are a fascinating reading. Ashby seems today, when the general ideas are buried under the sediment of narrow and technical papers, well ahead of his time because his model was, in essence, a 32 constrained by structure condensed matter, close to that of Ising, where topological neighbors ....

....Langdon, Peter Schuster, and many others) It studies the theoretical aspects of LMS, excluding the US Tax Code, the most complex creation of all. Ross Ashby captured the state of evolutionary divergence of the emergent AI into computer and life sciences in his An Introduction to Cybernetics [13]. In spite of Alan Turing s own biological interests, the Turing Machine gave a great impetus to AI toward computer science rather than life science. Nevertheless, the anthropomorphic Turing test was based on live human intelligence as the reference point and was, in essence, a test for ....

W. Ross Ashby, An Introduction to Cybernetics, London: Chapman & Hall, 1956/1964. (A short gracious bio: http://www.isss.org/lumashby.htm)

....or fuzzy. Deterministic (robust) part and additional black boxes acting on each output of object can represent them. The only information about these boxes is that they have limited values of output variables, which are similar to the corresponding states of object. According to Ashby [2] diversity of control system or model is to be not smaller, than diversity of the object itself. The Law of4dequateness, given by S.Beer, establishes that for optimal control the objects are to be compensated by corresponding black boxes of the control system [1] For optimal pattern recognition ....

Ashby D. An introduction to cybernetics. J. Wiley, New York 1958.

....likely that there is a link between the complexity of the coupled agent environment system and the complexity of the behaviours that can be exhibited. Behaviours of a certain complexity may require a minimum level of system complexity for their performance (compare Ashby s Law of Requisite Variety [2]) Further, it may be that there are different ways of distributing the complexity between the subsystems of agent and environment, as occurred with the circle formation task; the complexity may be situated in different subsystems in different proportions, provided that the complexity of the ....

Ashby, W.R. (1956) Introduction to Cybernetics. Chapman & Hall, London.

....firstly, if the various structures of the neural network can be generated and, secondly, if the best of them can be selected by a criterion of their efficiency. The variety or the number of the training neural network states must be adequate in accordance with the general principle of W. Ashby [2]. The complexity of the learned neural network will be optimal if its variety will be adequate under the minimal number of its nodes and their synaptic connections. For known F. Rosenblatt s perceptron consisting of the input (sensor) associative and adjustable layers of the nodes, the ....

Ashby, W.R., An Introduction to Cybernetics. Willey, New York, 1956.

....serves as a great source of inspiration to generative artists 11 . Artists are often looking for surprise, novelty, agency and that out of control feeling in their work, what Ashby describes as Descarte s Dictum: how can a designer build a device which outperforms the designer s specifications [2] Artists can get away with much more than scientists can where emergence is concerned, since Art is not bound by the same obligations as Science. But in gaining such freedom, the artist also acquires new problems because, in general, the search space lacks reference points and becomes ....

Ashby, W.R.: An Introduction to Cybernetics. London, Chapman & Hall (1956)

....this situation as the existence of a semiotic control system. We know briefly outline the theory of semiotic systems. 2. 1 Semiotic Models and Controls There is a rich literature (e.g. 5, 15, 17, 18, 19] traceable back to the founders of systems theory and cybernetics in the post war period [4], which has tried to construct a coherent philosophy of science based on two fundamental concepts: ffl Models as the basis not only for a consistent epistemology of systems, but also as an explanation of the special properties of living and cognitive systems. ffl Control systems as the ....

....engineering [2] and scientific domains. However, our normal sense of control combines it with models, which are used to aid in decisionmaking by predicting future states of anticipated actions, using prediction of future events to guide actions. This is what Ashby refers to as cause control [4], or Rosen as anticipatory [17] or Klir as feedforward [10] In this architecture an endo model embedded within a controlsystemis used to make a decision as to which action to take, and thus acts in the role of the agent. It is this view which most dominates our conception of the nature of ....

Ashby, Ross: (1956) Introduction to Cybernetics, Methuen, London, http://pcp.vub.ac.be/books/IntroCyb.pdf

....the paper. Nature vs. Open Systems To clarify the application field of chance discovery, we draw a broad distinction about the object of investigation: nature vs. open systems (Schurz 1999) Whereas nature is governed by natural laws, open systems are typically modeled abstractly by cybernetics (Ashby 1964) and system theory (v. Bertalan#y 1979) Examples of open systems include living systems such as human beings, scientific communities and companies, and artificial (or technical) systems, e.g. cars and power plants. Both kinds can be described by the following system theoretical (S1 2) and ....

Ashby, W. R. 1964. An Introduction to Cybernetics.

....caused a bifurcation between models and programs since the digital program is chock full of abstract entities. The connection of program to reality had become tenuous. Systems Theory [11, 57, 40] and its follow on principles of Systems Engineering [78, 68] beginning with the study of Cybernetics [76, 7], provided a uniform view of system. Specializations of systems to handle discrete events described systems with irregular time intervals [42, 81] which were more attuned to how programs tend to operate. A system is defined through a model and contains, input, output, state, as well as mapping ....

W. Ross Ashby. An Introduction to Cybernetics. John Wiley and Sons, 1963.

....idea 17 that the result of species interacting wi ll imply that the evolutionary development of one wi ll make the environment of the others more complex as it forms part of the environment. This in turn wi ll make it advantageous (according to something akin to Ashby s law of requisite variety [1]) for it to evolve more complex processes to cope. This in turn puts the pressure on the first species and so on. Such a process would necessarily increase the analytic complexity of the ecology w.r.t. the species, as well as the evolutionary fitness complexity of predicting the behaviour ....

Ashby,WR (1964): Introduction to Cybernetics. Methuen, New York.

....the robot body, and then checks whether that solution works for the specific environment and robot (e.g. sensors with a certain level of precision, obstacles of a given shape arranged in certain configurations, etc. Conversely, in artificial evolution constraints may be viewed as opportunities (Ashby 1956; Scheier et al. 1998) To better illustrate this point we will consider an experiment carried out by Miglino (Miglino 1996; see also Lund and Miglino 1998) where the author used artificial 16 evolution to train a Khepera robot to perform a navigation task that had been previously studied with ....

Ashby, W.R. (1956) An introduction to cybernetics. London, Chapman and Hall.

....I propose to introduce an extension of this concept: relational closure , which can be analysed mathematically and conceptually in a very simple way. In mathematical systems theories closure is understood as the invariance of a set under an algebra (e.g. a group) of transformations (cfr. Ashby, 1964). The problem with this definition is that there is an a priori separation between algebras (representing systems) individual transformations (representing subsystems or subprocesses) and sets. In a general self organizing complex it is not clear which features should be modelled as algebras and ....

Ashby W. R. (1964) : Introduction to Cybernetics, (Methuen, London).

....2 Nature vs. Open Systems To clarify the application field of chance discovery, we draw a broad distinction about the object of investigation: nature vs. open systems (Schurz [7] Whereas nature is governed by natural laws, open systems are typically modeled abstractly by cybernetics (Ashby [1]) and system theory (v. Bertalan#y [9] Examples of open systems include living systems such as human beings, scientific communities and companies, and artificial (or technical) systems, e.g. cars and power plants. Both kinds can be described by the following system theoretical (S1 2) and ....

W. R. Ashby. An Introduction to Cybernetics. London, 1964.

....methods than with aims or convictions. Where Campbell (1974) called his philosophy of knowledge evolutionary epistemology , I would characterize mine as evolutionary cybernetic epistemology (Heylighen, 1993) By cybernetic I refer to the broad domain of cybernetics and general systems theory (Ashby, 1956; von Bertalanffy, 1968) and its transdisciplinary study of organization, communication, control and modelling. This epistemology is part of the larger evolutionary cybernetic philosophy which, together with others, I am trying to develop in the Principia Cybernetica Project (Joslyn, Heylighen ....

Ashby W. R. (1956) Introduction to Cybernetics. Methuen, London.

....correlates to entropies, and correlates to such important results as Shannon s 10th Theorem and the Second Law of Thermodynamics were also sought in non thermodynamic contexts such as biology, ecology, psychology, sociology, and economics. One important result is Ashby s Law of Requisite Variety [3], which states that in a control system, the amount of information kept within the system places an upper bound on the amount of variety in the environment which the control system is able to counteract. Another is von Forster s analysis of self organization as a decrease in internal entropy, and ....

Ashby, Ross: (1956) Introduction to Cybernetics, Methuen, London

....drawn by people. Certainly, the making of distinctions] is the most fundamental act of systems theory, the very act of defining the system presently of interest, of distinguishing it from its environment [7] While this sense can be traced in the systems theory literature to Ashby [2] and Spencer Brown [4, 29] and it resonates with post modernism, constructivist epistemology, and second order cybernetics [31] it should be noted that it is also use in much of classical physics, beginning with thermodynamics, where a system is any quantity of matter, any region of space, ....

Ashby, Ross: (1956) Introduction to Cybernetics, Methuen, London

....be obtained by using rules, or combinations of rules, that are able to introduce variety more easily while they are active than the rules used so far. In other words, rules that tend not to get the system stuck in a small region of possible con gurations (cf. Ashby s Law of Requisite Variety, Ashby, 1956, Ch 11) This could be achieved by implementing both postsynaptic and presynaptic regulation of plasticity and adding noise. Other possibilities of activity dependent plasticity include modulatory synapses and volume modulation in which the release of di usible chemicals can a ect the ....

Ashby, W. R. (1956). Introduction to Cybernetics. London: Chapman and Hall, second edition.

....the war time and post war development of the rst modern computers came a surge of research into computational theory. Seminal work by mathematicians such as McCulloch and Pitts (1943) on the logic of neural circuitry, Turing (1952) on di usion reaction models of morphogenesis, Walter (1963) and Ashby (1956) on cybernetics, von Neumann and Burks (1966) on automata theory and self replication, and later Holland (1975) on the formal properties of adaptation, involved the application of logic, mathematics, robotics, and control theory to essentially biological problems. The above cited pieces of ....

Ashby, W. R. (1956). An Introduction to Cybernetics. Chapman & Hall, London.

....classifying agents and environments (e.g. Littman, 1993; Wilson, 1991) 2. Systems 2.1 Definition There is no single established definition of systems (van Gelder, 1998, p. 618) Here we adopt a definition that seems to formally capture the basic ideas generally associated with systems (see Ashby, 1956; van Gelder Port, 1995; van Gelder, 1998) A system is defined by specifying: ffl I , an input space, ffl O, an output space, ffl S, a state space, ffl T = t 0 ; t 1 ; an ordered list of moments in time, ffl s 0 2 S and o 0 2 O, the state and output at t 0 , ffl StateTrans : I ....

....and the output is set to o x = Output(i x ; s x ) StateTrans and Output may be deterministic or stochastic. A closed system is a system with an empty input space and an empty output space. All other systems are open systems. Time is discretized to allow certain measures to be simply counted (Ashby, 1956) and to facilitate presentation of the arguments. The variables in I , O, and S may be continuous, but for computer simulation, which Adaptive Behavior research is concerned with, they are approximated with a discrete representation. Note that this definition is very general, encompassing systems ....

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Ashby, W. R. (1956). An introduction to cybernetics. London: Chapman and Hall.

....control mechanisms as well as self initiated technical (i.e. endogenous) control mechanisms. Thanks to the cybernetic theory we now know that the behaviour of many organisms depends first and foremost on its own self regulatory mechanisms and only indirectly upon exogenous regulatory mechanisms [2]. One may conclude that, the effectiveness and efficiency of exogenous control mechanisms depends crucially on the extent to which they are able to appropriately shape the self regulatory behaviour of the organism being controlled. Exogenous control mechanisms, in and by themselves, are almost ....

Ashby, W. R. An Introduction to Cybernetics, Chapman & Hall, London, 1956.

....about classifying agents and environments #e.g. Littman, 1993; Wilson, 1991#. 2. Systems 2.1 De#nition There is no single established de#nition of systems #van Gelder, 1998, p. 618#. Here we adopt a de#nition that seems to formally capture the basic ideas generally associated with systems #see Ashby, 1956; van Gelder Port, 1995; van Gelder, 1998#. A system is de#ned by specifying: # I , an input space, # O, an output space, # S, a state space, # T =#t 0 ;t 1 ; #, an ordered list of moments in time, # s 0 2 S and o 0 2 O, the state and output at t 0 , # StateTrans : I # S S, the state ....

....and the output is set to o x = Output#i x ;s x #: StateTrans and Output may be deterministic or stochastic. A closed system is a system with an empty input space and an empty output space. All other systems are open systems. Time is #discretized to allow certain measures to be simply counted #Ashby, 1956# and to facilitate presentation of the arguments. The variables in I , O, and S may be continuous, but for computer simulation, which Adaptive Behavior research is concerned with, they are approximated with a discrete representation. Note that this de#nition is very general, encompassing systems ....

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Ashby, W. R. #1956#. An introduction to cybernetics. London: Chapman and Hall.

....argued that there are both formal and non formal structural factors that affect the change process. When related to barriers to change, formal barriers are those which directly depend on the formal organizational structure. Every organization has to have some degree of hierarchy (Ackoff 1974; Ashby 1956; Aulin 1982) However, organizational hierarchy can also lead to inflexibility, resistance to change, and slow reactions. Deep hierarchy indicates vertical communication and centralized decision making. Such organization makes it difficult to see the need for change. Thus changes take place ....

Ashby, R. W. An Introduction to Cybernetics, Chapman & Hall, London, 1956.

.... (Atthill 1975; Miser Quade 1985) Systems Engineering (Hall 1962; Jenkins 1969) Systems Dynamics (Forrester 1961, 1971) General Systems Theory (von Bertalanffy 1968; Mesarovic, et al. 1975; Le Moigne 1977 1994; Rapoport 1986) Living Systems Theory (Miller 1978) Cybernetics (Wiener 1948; Ashby 1956, 1960) Viable System Model (Beer 1959, 1966, 1974, 1979, 1981) Soft System Methodology (Checkland 1978, 1981; Checkland Scholes 1990) Interactive Planning (Ackoff 1981a, 1981b) Social Systems Design (Churchman 1971, 1979a, 1979b) Strategic Assumptions Surfacing and Testing (Mason Mitroff ....

....[OR MS] Churchman et al. 1957; Ackoff Sasieni 1968) Systems Analysis [SA] Atthill 1975; Miser Quade 1985) Systems Engineering [SE] Hall 1962; Jenkins 1969) Systems Dynamics [SD] Forrester 1961, 1971) Cybernetics including both first order cybernetics [1 st Cyb. Wiener 1948; Ashby 1956, 1960) and second order cybernetics 3 [2 nd Cyb. von Foerster 1984; von Glaserfeld 1984, 1995) General Systems Theory [GST] von Bertalanffly 1968) Living Systems Theory [LST] Miller 1978) Viable Systems Model [VSM] Beer 1974, 1979, 1981) Autopoietic Systems Theory [AST] ....

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Ashby, W.R. (1956). An Introduction to Cybernetics. Chapman & Hall, London.

....and artificial or technical systems, the objects of technology. Abstractly, both kinds of systems share the following features (Si for system theory, Ci for cybernetics) 3 2 To my knowledge this distinction was first introduced by my father J. Schurz (1990) 3 Cybernetics has been founded by Ashby (1964), system theory by Bertalanffy 5 S1) Open systems are physical ensembles composed of parts, placed into a (physical) environment significantly larger than themselves. There is continuous exchange of energy and matter between system and environment. The environment has resources to satisfy the ....

Ashby, W. R. (1964): An Introduction to Cybernetics (2nd ed.), London.

....actors operate, are significantly different and more prone to distortion in crisis situations. Enactment requires, and also helps, individuals make sense of the organization by enabling people to join in the conventional, cultural and normative processes and to design a meaningful place (Ashby, 1952, 1960). In this sense, the rationality of the organization is a post hoc interpretation of events or a symbolic product that is constructed through actions that in themselves are non rational (Brown, 1978, p. 370) Thus, leadership and organizational learning are both contextually defined and ....

Ashby, W.R. (1960), An Introduction to Cybernetics, Chapman & Hall, London.

....or is at least a candidate for mathematical formalization; a scientific metaphysics is one which bears upon draws from and or contributes to one or more scientific disciplines. Bunge s conception is close to views of von Bertalanffy (1968) Wiener (1950) Boulding (1956) Rapoport (1986) Ashby (1956), Klir (1991) and many others. ISSN 1078 6236 c fl 1995 International Institute for General Systems Studies 2 M. Zwick ASSA Special Issue Bunge applied this characterization specifically to game theory, automata theory, and other long established systems and cybernetic theories, but it applies ....

Ashby, W. R. (1956). An Introduction to Cybernetics. London: Methuen.

....of this paper is to revisite homeostasis as a basic concept and discuss its relation to stability in terms of dynamical systems theory. We investigate a model in which a cell, as well an organ or an organism, is represented as a self regulating unit similar to that of a homeostat proposed by R. W. Ashby [Ashby, 1952]. A similar abstract model is discussed, for example, in [Adolph, 1964] In order to show that this kind of scheme can be found to be realized analogously on different levels of biological organization, we refer to three very well known examples: an unicellular organism, namely Dictyostelium, a ....

Ashby, W. R. (1952): An Introduction to Cybernetics. John Wiley, New York.

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Ashby, R. (1956) Introduction to cybernetics. John Wiley: NewYork.

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W. Ross Ashby, An Introduction to Cybernetics, Chapman & Hill, London, 1956.

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W. Ross Ashby, An Introduction to Cybernetics, Chapman & Hill, London, 1956.

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W. Ross Ashby, "An Introduction to Cybernetics", 4th impression, Chapman & Hall Ltd., London, 1961

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Ashby, W.R., 1956. An Introduction to Cybernetics. Chapman and Hall, London.

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R. Ashby, An Introduction to Cybernetics. London: Chapman and Hall, 1957.

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Ashby,W.R.:An Introduction to Cybernetics. Chapman and Hall, London 1956. Internet (1999): http://pcp.vub.ac.be/books/IntroCyb.pdf

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Ashby, W.R., 1956. An Introduction to Cybernetics. Chapman and Hall, London.

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Ashby, W. R. (1957), `An Introduction to Cybernetics', Chapman and Hall, London. Internet URL (1999): http://pcp.vub.ac.be/ books/IntroCyb.pdf

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Ashby, W. R. (1958). An introduction to cybernetics. London: Chapman and Hall.

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Ashby, Ross: (1956) Introduction to Cybernetics, Methuen, London, http://pcp.vub.ac.be/books/IntroCyb.pdf

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Ashby, R (1956), Introduction to Cybernetics, London, Chapman and Hall

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Ashby, Ross. An Introduction to Cybernetics. London: Methuen. 1956.

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Ashby, W. Ross, An Introduction to Cybernetics, Methuen, London, (1956).

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Ashby, W.R. 1976 An Introduction to Cybernetics. London: Methuen.

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Ashby, W.R.: An introduction to cybernetics. (1956) London: Chapman and Hall.

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Ashby, W. R. (1956). An Introduction to Cybernetics. London: Chapman & Hall.

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