Winner of the CHOICE Outstanding Academic Title of the Choice ACRL
Outstanding Academic Title, Choice
Cybernetics—the science of communication and control as it applies to machines and to humans—originates from efforts during World War II to build automatic antiaircraft systems. Following the war, this science extended beyond military needs to examine all systems that rely on information and feedback, from the level of the cell to that of society. In The Cybernetics Moment, Ronald R. Kline, a senior historian of technology, examines the intellectual and cultural history of cybernetics and information theory, whose language of “information,” “feedback,” and “control” transformed the idiom of the sciences, hastened the development of information technologies, and laid the conceptual foundation for what we now call the Information Age.
Kline argues that, for about twenty years after 1950, the growth of cybernetics and information theory and ever-more-powerful computers produced a utopian information narrative—an enthusiasm for information science that influenced natural scientists, social scientists, engineers, humanists, policymakers, public intellectuals, and journalists, all of whom struggled to come to grips with new relationships between humans and intelligent machines.
Kline traces the relationship between the invention of computers and communication systems and the rise, decline, and transformation of cybernetics by analyzing the lives and work of such notables as Norbert Wiener, Claude Shannon, Warren McCulloch, Margaret Mead, Gregory Bateson, and Herbert Simon. Ultimately, he reveals the crucial role played by the cybernetics moment—when cybernetics and information theory were seen as universal sciences—in setting the stage for our current preoccupation with information technologies.
Artificial Intelligence: A Modern Approach, 3e offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.
Dr. Peter Norvig, contributing Artificial Intelligence author and Professor Sebastian Thrun, a Pearson author are offering a free online course at Stanford University on artificial intelligence.
According to an article in The New York Times , the course on artificial intelligence is “one of three being offered experimentally by the Stanford computer science department to extend technology knowledge and skills beyond this elite campus to the entire world.” One of the other two courses, an introduction to database software, is being taught by Pearson author Dr. Jennifer Widom.
Artificial Intelligence: A Modern Approach, 3e is available to purchase as an eText for your Kindle™, NOOK™, and the iPhone®/iPad®.
This book constitutes the refereed proceedings of the Cybernetics and Mathematics Applications in Intelligent Systems Section of the 6th Computer Science On-line Conference 2017 (CSOC 2017), held in April 2017.
It brings new approaches and methods to real-world problems and exploratory research that describes novel approaches in the cybernetics, algorithms and software engineering in the scope of the intelligent systems.
This book constitutes the refereed proceedings of the Computational Methods in Systems and Software 2017, a conference that provided an international forum for the discussion of the latest high-quality research results in all areas related to computational methods, statistics, cybernetics and software engineering.
This book has been created for data scientists who want to see machine learning in action and explore its real-world application. With guidance on everything from the fundamentals of machine learning and predictive analytics to the latest innovations set to lead the big data revolution into the future, this is an unmissable resource for anyone dedicated to tackling current big data challenges. Knowledge of programming (Python and R) and mathematics is advisable if you want to get started immediately.What You Will Learn
Finding meaning in increasingly larger and more complex datasets is a growing demand of the modern world. Machine learning and predictive analytics have become the most important approaches to uncover data gold mines. Machine learning uses complex algorithms to make improved predictions of outcomes based on historical patterns and the behaviour of data sets. Machine learning can deliver dynamic insights into trends, patterns, and relationships within data, immensely valuable to business growth and development.
This book explores an extensive range of machine learning techniques uncovering hidden tricks and tips for several types of data using practical and real-world examples. While machine learning can be highly theoretical, this book offers a refreshing hands-on approach without losing sight of the underlying principles. Inside, a full exploration of the various algorithms gives you high-quality guidance so you can begin to see just how effective machine learning is at tackling contemporary challenges of big data.
This is the only book you need to implement a whole suite of open source tools, frameworks, and languages in machine learning. We will cover the leading data science languages, Python and R, and the underrated but powerful Julia, as well as a range of other big data platforms including Spark, Hadoop, and Mahout. Practical Machine Learning is an essential resource for the modern data scientists who want to get to grips with its real-world application.
With this book, you will not only learn the fundamentals of machine learning but dive deep into the complexities of real world data before moving on to using Hadoop and its wider ecosystem of tools to process and manage your structured and unstructured data.
You will explore different machine learning techniques for both supervised and unsupervised learning; from decision trees to Naive Bayes classifiers and linear and clustering methods, you will learn strategies for a truly advanced approach to the statistical analysis of data. The book also explores the cutting-edge advancements in machine learning, with worked examples and guidance on deep learning and reinforcement learning, providing you with practical demonstrations and samples that help take the theory–and mystery–out of even the most advanced machine learning methodologies.Style and approach
A practical data science tutorial designed to give you an insight into the practical application of machine learning, this book takes you through complex concepts and tasks in an accessible way. Featuring information on a wide range of data science techniques, Practical Machine Learning is a comprehensive data science resource.
IMA - Institute of Information Management in Mechanical Engineering
ZLW - Center for Learning and Knowledge Management
IfU - Associated Institute for Management Cybernetics e.V. Faculty of Mechanical Engineering, RWTH Aachen University
The book presents a range of innovative fields of application, including: cognitive systems, cyber-physical production systems, robotics, automation technology, machine learning, natural language processing, data mining, predictive data analytics, visual analytics, innovation and diversity management, demographic models, virtual and remote laboratories, virtual and augmented realities, multimedia learning environments, organizational development and management cybernetics. The contributions selected reflect the fundamental paradigm shift toward an increasingly interdisciplinary research world – which has always been both the basis and spirit of the institute cluster IMA/ZLW & IfU.
Principles of Artificial Intelligenceevolved from the author's courses and seminars at Stanford University and University of Massachusetts, Amherst, and is suitable for text use in a senior or graduate AI course, or for individual study.
Designing Freedom ponders the possibilities of liberty in a cybernetic world.
As lives offline and online merge even more, it is easy to forget how we got here. Rise of the Machines reclaims the spectacular story of cybernetics, one of the twentieth century’s pivotal ideas.
Springing from the mind of mathematician Norbert Wiener amid the devastation of World War II, the cybernetic vision underpinned a host of seductive myths about the future of machines. Cybernetics triggered blissful cults and military gizmos, the Whole Earth Catalog and the air force’s foray into virtual space, as well as crypto-anarchists fighting for internet freedom.
In Rise of the Machines, Thomas Rid draws on unpublished sources—including interviews with hippies, anarchists, sleuths, and spies—to offer an unparalleled perspective into our anxious embrace of technology.
• How does a machine learn a new concept on the basis of examples?
• How can a neural network, after sufficient training, correctly predict the outcome of a previously unseen input?
• How much training is required to achieve a specified level of accuracy in the prediction?
• How can one identify the dynamical behaviour of a nonlinear control system by observing its input-output behaviour over a finite interval of time?
In its successful first edition, A Theory of Learning and Generalization was the first book to treat the problem of machine learning in conjunction with the theory of empirical processes, the latter being a well-established branch of probability theory. The treatment of both topics side-by-side leads to new insights, as well as to new results in both topics.
This second edition extends and improves upon this material, covering new areas including:
• Support vector machines.
• Fat-shattering dimensions and applications to neural network learning.
• Learning with dependent samples generated by a beta-mixing process.
• Connections between system identification and learning theory.
• Probabilistic solution of 'intractable problems' in robust control and matrix theory using randomized algorithm.
Reflecting advancements in the field, solutions to some of the open problems posed in the first edition are presented, while new open problems have been added.
Learning and Generalization (second edition) is essential reading for control and system theorists, neural network researchers, theoretical computer scientists and probabilist.
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.
Three groups of problems of the new cybernetics are considered in the book:
(a) Systems that can be calculated based on known physics of subsystems. This includes the external observer influence calculated from basic physical laws (ideal dynamics) and dynamics of a physical system influenced even by low noise (observable dynamics).
(b) Emergent systems. This includes external noise from the observer by using the black box model (complex dynamics), external noise from the observer by using the observer’s intuition (unpredictable dynamics), defining boundaries of application of scientific methods for system behavior prediction, and the role of the observer’s intuition for unpredictable systems.
(c) Methods for solution of basic physical paradoxes by using methods of the new cybernetics: the entropy increase paradox, Schrödinger’s cat paradox (wave package reduction in quantum mechanics), the black holes information paradox, and the time wormholes grandfather paradox. All of the above paradoxes have the same resolution based on the principles of new cybernetics. Indeed, even a small interaction of an observer with an observed system results in their time arrows’ alignment (synchronization) and results in the paradox resolution and appearance of the universal time arrow.
This monograph is the second edition in the series, providing the reader with a selection of high-quality papers dedicated to current progress, new developments and research trends in man-machine interactions area. In particular, the topical subdivisions of this volume include human-computer interfaces, robot control and navigation systems, bio-data analysis and mining, pattern recognition for medical applications, sound, text and image processing, design and decision support, rough and fuzzy systems, crisp and fuzzy clustering, prediction and regression, algorithms and optimisation, and data management systems.
Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include:
Exploring issues at the heart of the subject, this book is suitable for anyone interested in AI, and provides an illuminating and accessible introduction to this fascinating subject.
In response to the apparent dissolution of boundaries at work in the contemporary technosciences of emergence, neocybernetics observes that cognitive systems are operationally bounded, semi-autonomous entities coupled with their environments and other systems. Second-order systems theory stresses the recursive complexities of observation, mediation, and communication. Focused on the neocybernetic contributions of von Foerster, Francisco Varela, and Niklas Luhmann, this collection advances theoretical debates about the cultural, philosophical, and literary uses of their ideas. In addition to the interview with von Foerster, Emergence and Embodiment includes essays by Varela and Luhmann. It engages with Humberto Maturana’s and Varela’s creation of the concept of autopoiesis, Varela’s later work on neurophenomenology, and Luhmann’s adaptations of autopoiesis to social systems theory. Taken together, these essays illuminate the shared commitments uniting the broader discourse of neocybernetics.
Contributors. Linda Brigham, Bruce Clarke, Mark B. N. Hansen, Edgar Landgraf, Ira Livingston, Niklas Luhmann, Hans-Georg Moeller, John Protevi, Michael Schiltz, Evan Thompson, Francisco J. Varela, Cary Wolfe
Mindell examines four different arenas of control systems research in the United States between the world wars: naval fire control, the Sperry Gyroscope Company, the Bell Telephone Laboratories, and Vannevar Bush's laboratory at MIT. Each of these institutional sites had unique technical problems, organizational imperatives, and working environments, and each fostered a distinct engineering culture. Each also developed technologies to represent the world in a machine.
At the beginning of World War II, President Roosevelt established the National Defense Research Committee, one division of which was devoted to control systems. Mindell shows how the NDRC brought together representatives from the four pre-war engineering cultures, and how its projects synthesized conceptions of control, communications, and computing. By the time Wiener articulated his vision, these ideas were already suffusing through engineering. They would profoundly influence the digital world.
As a new way to conceptualize the history of computing, this book will be of great interest to historians of science, technology, and culture, as well as computer scientists and theorists. Between Human and Machine: Feedback, Control, and Computing before Cybernetics
This wickedly inventive guide offers 19 build-it-yourself projects featuring high-tech devices that can map, manipulate, and even improve the greatest computer on earth-the human brain. Every project inside Mind Performance Projects for the Evil Genius is perfectly safe and explores cutting-edge concepts, such as brain wave mapping, lucid dream control, and hypnosis.
Using easy-to-find parts and tools, this do-it-yourself book offers a wide variety of brain-bending bio hacks you can accomplish on your own. You'll find detailed guidelines, parameters, schematics, code, and customization tips for each project in the book. The only limit is your imagination!
Mind Performance Projects for the Evil Genius:
Build these and other lid-flipping gadgets: