Author: Norbert Wiener
Publisher: MIT Press
Release Date: 1965
"This book represents the outcome, after more than a decade, of a program of work undertaken jointly with Dr. Arturo Rosenblueth. The author and Rosenbleuth, as well as other scientists, became aware of the essential unity of the set of problems centering about communication, control, and statistical mechanics, whether in the machine or in living tissue. They were also hampered by the lack of unity of the literature concerning these problems, and by the absence of any common terminology. They decided to call the entire field of control and communication theory, whether in the machine or in the animal, by the name cybernetics. This book focuses on cybernetics, from its earlier history with computing machines to its more modern uses. This second edition includes both the first edition from 1846 and supplementary chapters from 1961"--Introduction. (PsycINFO Database Record (c) 2010 APA, all rights reserved).
Die Beiträge des Sammelbandes befassen sich mit zentralen Themen der Kybernetik: Was ist Kybernetik überhaupt? Wie können wir sie nutzen und wo können wir sie einsetzen? Die Autoren zeigen, dass unser Digitalzeitalter von umfassenden technologischen Neuerungen, komplexer Vernetzung und schnellen Innovationszyklen gekennzeichnet ist, die sich klassischen Beschreibungsmodellen und traditionellen Regelungsmechanismen entziehen. Immer vielfältiger interagierende Strukturen erfordern neue Methoden, um diese Komplexität zu beschreiben und zu gestalten. Hochkarätige WissenschaftlerInnen verschiedenster Fachgebiete erläutern die Kybernetik aus Sicht ihrer jeweiligen Disziplin.
Author: J.A. Tenreiro Machado
Publisher: Springer Science & Business Media
Release Date: 2008-12-18
Engineering practice often has to deal with complex systems of multiple variable and multiple parameter models almost always with strong non-linear coupling. The conventional analytical techniques-based approaches for describing and predicting the behaviour of such systems in many cases are doomed to failure from the outset, even in the phase of the construction of a more or less appropriate mathematical model. These approaches normally are too categorical in the sense that in the name of “modelling accuracy” they try to describe all the structural details of the real physical system to be modelled. This can significantly increase the intricacy of the model and may result in a enormous computational burden without achieving considerable improvement of the solution. The best paradigm exemplifying this situation may be the classic perturbation theory: the less significant the achievable correction, the more work has to be invested to obtain it. A further important component of machine intelligence is a kind of “structural uniformity” giving room and possibility to model arbitrary particular details a priori not specified and unknown. This idea is similar to the ready-to-wear industry, which introduced products, which can be slightly modified later on in contrast to tailor-made creations aiming at maximum accuracy from the beginning. These subsequent corrections can be carried out by machines automatically. This “learning ability” is a key element of machine intelligence. The past decade confirmed that the view of typical components of the present soft computing as fuzzy logic, neural computing, evolutionary computation and probabilistic reasoning are of complementary nature and that the best results can be applied by their combined application. Today, the two complementary branches of Machine Intelligence, that is, Artificial Intelligence and Computational Intelligence serve as the basis of Intelligent Engineering Systems. The huge number of scientific results published in Journal and conference proceedings worldwide substantiates this statement. The present book contains several articles taking different viewpoints in the field of intelligent systems.
This book is a concise navigator across the history of cybernetics, its state-of-the-art and prospects. The evolution of cybernetics (from N. Wiener to the present day) and the reasons of its ups and downs are presented. The correlation of cybernetics with the philosophy and methodology of control, as well as with system theory and systems analysis is clearly demonstrated. The book presents a detailed analysis focusing on the modern trends of research in cybernetics. A new development stage of cybernetics (the so-called cybernetics 2.0) is discussed as a science on general regularities of systems organization and control. The author substantiates the topicality of elaborating a new branch of cybernetics, i.e. organization theory which studies an organization as a property, process and system. The book is intended for theoreticians and practitioners, as well as for students, postgraduates and doctoral candidates. In the first place, the target audience includes tutors and lecturers preparing courses on cybernetics, control theory and systems science.
Author: Daniel S. Yeung
Publisher: Springer Science & Business Media
Release Date: 2006-04-18
This book constitutes the thoroughly refereed post-proceedings of the 4th International Conference on Machine Learning and Cybernetics, ICMLC 2005, held in Guangzhou, China in August 2005. The 114 revised full papers of this volume are organized in topical sections on agents and distributed artificial intelligence, control, data mining and knowledge discovery, fuzzy information processing, learning and reasoning, machine learning applications, neural networks and statistical learning methods, pattern recognition, vision and image processing.
Author: Thomas O. Williams
Publisher: Nova Publishers
Release Date: 2007-01
Biological cybernetics includes experimental, theoretical and application-oriented aspects of information processing in organisms, including sensory, motor, cognitive, and ecological phenomena. This book presents research from around the world in this field.
Author: G. Vijver
Publisher: Springer Science & Business Media
Release Date: 2013-06-29
Gertrudis Van de Vijver· Seminar of Logic and Epistemology University of Ghent Before being classified under the fashionable denominators of complexity and chaos, self-organization and autonomy were intensely inquired into in the cybernetic tradition. Despite all rejections that cybernetics has gone through in the second half of this century, today its importance is more and more recognized. Its decisive influence for connectionist theories, autopoietic and constructivist theories, for different forms of applied or experimental epistemology, is being more and more understood and generally accepted. It is mainly due to the success of connectionist models that we observe today a revival of interest for cybernetics. The 1943 article by McCulloch and Pitts is evidently a founding article. Cybernetics has however a much broader interest than the one linked to technical-mathematical details relevant to the construction of networks. For instance, the evolution from first to second order cybernetics, the ways of approaching biological and cognitive phenomena in the latter and the limits that were formulated there, are particularly meaningful to understand current developments and divergences in connectionism. A nuanced picture of cybernetic's history and its present state is therefore clearly epistemologically essential.
Author: Alex M. Andrew
Publisher: Springer Science & Business Media
Release Date: 2009-04-21
In this book I argue that a reason for the limited success of various studies under the general heading of cybernetics is failure to appreciate the importance of con- nuity, in a simple metrical sense of the term. It is with particular, but certainly not exclusive, reference to the Arti cial Intelligence (AI) effort that the shortcomings of established approaches are most easily seen. One reason for the relative failure of attempts to analyse and model intelligence is the customary assumption that the processing of continuous variables and the manipulation of discrete concepts should be considered separately, frequently with the assumption that continuous processing plays no part in thought. There is much evidence to the contrary incl- ing the observation that the remarkable ability of people and animals to learn from experience nds similar expression in tasks of both discrete and continuous nature and in tasks that require intimate mixing of the two. Such tasks include everyday voluntary movement while preserving balance and posture, with competitive games and athletics offering extreme examples. Continuous measures enter into many tasks that are usually presented as discrete. In tasks of pattern recognition, for example, there is often a continuous measure of the similarity of an imposed pattern to each of a set of paradigms, of which the most similar is selected. The importance of continuity is also indicated by the fact that adjectives and adverbs in everyday verbal communication have comparative and superlative forms.
The subject “Systems sciences and cybernetics” is the outcome of the convergence of a number of trends in a larger current of thought devoted to the growing complexity of (primarily social) objects and arising in response to the need for globalized treatment of such objects. This has been magnified by the proliferation and publication of all manner of quantitative scientific data on such objects, advances in the theories on their inter-relations, the enormous computational capacity provided by IT hardware and software and the critical revisiting of subject-object interaction, not to mention the urgent need to control the efficiency of complex systems, where “efficiency” is understood to mean the ability to find a solution to many social problems, including those posed on a planetary scale. The result has been the forging of a new, academically consolidated scientific trend going by the name of Systems Theory and Cybernetics, with a comprehensive, multi-disciplinary focus and therefore apt for understanding realities still regarded to be inescapably chaotic. This subject entry is subdivided into four sections. The first, an introduction to systemic theories, addresses the historic development of the most commonly used systemic approaches, from new concepts such as the so-called “geometry of thinking” or the systemic treatment of “non-systemic identities” to the taxonomic, entropic, axiological and ethical problems deriving from a general “systemic-cybernetic” conceit. Hence, the focus in this section is on the historic and philosophical aspects of the subject. Moreover, it may be asserted today that, beyond a shadow of a doubt, problems, in particular problems deriving from human interaction but in general any problem regardless of its nature, must be posed from a systemic perspective, for otherwise the obstacles to their solution are insurmountable. Reaching such a perspective requires taking at least the following well-known steps: a) statement of the problem from the determinant variables or phenomena; b) adoption of theoretical models showing the interrelationships among such variables; c) use of the maximum amount of – wherever possible quantitative – information available on each; d) placement of the set of variables in an environment that inevitably pre-determines the problem. That epistemology would explain the substantial development of the systemic-cybernetic approach in recent decades. The articles in the second section deal in particular with the different methodological approaches developed when confronting real problems, from issues that affect humanity as a whole to minor but specific questions arising in human organizations. Certain sub-themes are discussed by the various authors – always from a didactic vantage –, including: problem discovery and diagnosis and development of the respective critical theory; the design of ad hoc strategies and methodologies; the implementation of both qualitative (soft system methodologies) and formal and quantitative (such as the “General System Problem Solver” or the “axiological-operational” perspective) approaches; cross-disciplinary integration; and suitable methods for broaching psychological, cultural and socio-political dynamisms. The third section is devoted to cybernetics in the present dual meaning of the term: on the one hand, control of the effectiveness of communication and actions, and on the other, the processes of self-production of knowledge through reflection and the relationship between the observing subject and the observed object when the latter is also observer and the former observed. Known as “second order cybernetics”, this provides an avenue for rethinking the validity of knowledge, such as for instance when viewed through what is known as “bipolar feedback”: processes through which interactions create novelty, complexity and diversity. Finally, the fourth section centres around artificial and computational intelligence, addressing sub-themes such as “neural networks”, the “simulated annealing” that ranges from statistical thermodynamics to combinatory problem-solving, such as in the explanation of the role of adaptive systems, or when discussing the relationship between biological and computational intelligence.