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Neural Approximations for Optimal Control and Decision provides a comprehensive methodology for the approximate solution of functional optimization problems using neural networks and other nonlinear approximators where the use of traditional optimal control tools is prohibited by complicating factors like non-Gaussian noise, strong nonlinearities, large dimension of state and control vectors, etc. Features of the text include: * a general functional optimization framework; * thorough illustration of recent theoretical insights into the approximate solutions of complex functional optimization problems; * comparison of classical and neural-network based methods of approximate solution; * bounds to the errors of approximate solutions; * solution algorithms for optimal control and decision in deterministic or stochastic environments with perfect or imperfect state measurements over a finite or infinite time horizon and with one decision maker or several; * applications of current interest: routing in communications networks, traffic control, water resource management, etc.; and * numerous, numerically detailed examples. The authors' diverse backgrounds in systems and control theory, approximation theory, machine learning, and operations research lend the book a range of expertise and subject matter appealing to academics and graduate students in any of those disciplines together with computer science and other areas of engineering.
This book emerged out of international conferences organized as part of the AAAI Fall Symposia series, and the Swarmfest 2017 conference. It brings together researchers from diverse fields studying these complex systems using CAS and agent-based modeling tools and techniques. In the past, the knowledge gained in each domain has largely remained exclusive to that domain. By bringing together scholars who study these phenomena, the book takes knowledge from one domain to provide insight into others. Most interesting phenomena in natural and social systems include constant transitions and oscillations among their various phases - wars, companies, societies, markets, and humans rarely stay in a stable, predictable state for long. Randomness, power laws, and human behavior ensure that the future is both unknown and challenging. How do events unfold? When do they take hold? Why do some initial events cause an avalanche while others do not? What characterizes these events? What are the thresholds that differentiate a sea change from a non-event? Complex adaptive systems (CAS) have proven to be a powerful tool for exploring these and other related phenomena. The authors characterize a general CAS model as having a large number of self-similar agents that: 1) utilize one or more levels of feedback; 2) exhibit emergent properties and self-organization; and 3) produce non-linear dynamic behavior. Advances in modeling and computing technology have led not only to a deeper understanding of complex systems in many areas, but they have also raised the possibility that similar fundamental principles may be at work across these systems, even though the underlying principles may manifest themselves differently.
Advanced undergraduates and graduate students of electrical, chemical, mechanical, and environmental engineering will appreciate this text for a course in systems identification. In addition to the theoretical basis for mathematical modeling, it covers a variety of tried-and-true identification algorithms and their applications. Moreover, its broad view and fairly modest mathematical level offer readers a quick appraisal of established methods and their limitations. In addition to surveys covering classical methods of identification -- including impulse, step, and sine-wave testing -- and identification based on correlation function, the text examines least-squares model fitting, statistical properties of estimators, optimal estimation, and Bayes and maximum-likelihood estimators. Other topics include experiment design and choice of model structure as well as model validation. Numerical examples show students how to apply the modeling theories, and a chapter on specialized topics introduces research areas.
Niklas Luhmann ranks as one of the most important sociologists and social theorists of the twentieth century. Through his many books he developed a highly original form of systems theory that has been hugely influential in a wide variety of disciplines.
In "Introduction to Systems Theory," Luhmann explains the key ideas of general and sociological systems theory and supplies a wealth of examples to illustrate his approach. The book offers a wide range of concepts and theorems that can be applied to politics and the economy, religion and science, art and education, organization and the family. Moreover, Luhmann's ideas address important contemporary issues in such diverse fields as cognitive science, ecology, and the study of social movements.
This book provides all the necessary resources for readers to work through the foundations of systems theory - no other work by Luhmann is as clear and accessible as this. There is also much here that will be of great interest to more advanced scholars and practitioners in sociology and the social sciences.
An early text from Tiqqun that views cybernetics as a fable of late capitalism, and offers tools for the resistance. The cybernetician's mission is to combat the general entropy that threatens living beings, machines, societies-that is, to create the experimental conditions for a continuous revitalization, to constantly restore the integrity of the whole. -from The Cybernetic Hypothesis This early Tiqqun text has lost none of its pertinence. The Cybernetic Hypothesis presents a genealogy of our "technical" present that doesn't point out the political and ethical dilemmas embedded in it as if they were puzzles to be solved, but rather unmasks an enemy force to be engaged and defeated. Cybernetics in this context is the tekne of threat reduction, which unfortunately has required the reduction of a disturbing humanity to packets of manageable information. Not so easily done. Not smooth. A matter of civil war, in fact. According to the authors, cybernetics is the latest master fable, welcomed at a certain crisis juncture in late capitalism. And now the interesting question is: Has the guest in the house become the master of the house? The "cybernetic hypothesis" is strategic. Readers of this little book are not likely to be naive. They may be already looking, at least in their heads, for a weapon, for a counter-strategy. Tiqqun here imagines an unbearable disturbance to a System that can take only so much: only so much desertion, only so much destituent gesture, only so much guerilla attack, only so much wickedness and joy.
Adopting a cross-disciplinary approach, the review character of this monograph sets it apart from specialized journals. The editor is advised by a first-class board of international scientists, such that the carefully selected and invited contributions represent the latest and most relevant findings. The resulting review uses a common language and enables both researchers and newcomers in both natural and social science as well as engineering to access the most important results.
Automating technologies threaten to usher in a workless future. But this can be a good thing-if we play our cards right. Human obsolescence is imminent. The factories of the future will be dark, staffed by armies of tireless robots. The hospitals of the future will have fewer doctors, depending instead on cloud-based AI to diagnose patients and recommend treatments. The homes of the future will anticipate our wants and needs and provide all the entertainment, food, and distraction we could ever desire. To many, this is a depressing prognosis, an image of civilization replaced by its machines. But what if an automated future is something to be welcomed rather than feared? Work is a source of misery and oppression for most people, so shouldn't we do what we can to hasten its demise? Automation and Utopia makes the case for a world in which, free from need or want, we can spend our time inventing and playing games and exploring virtual realities that are more deeply engaging and absorbing than any we have experienced before, allowing us to achieve idealized forms of human flourishing. The idea that we should "give up" and retreat to the virtual may seem shocking, even distasteful. But John Danaher urges us to embrace the possibilities of this new existence. The rise of automating technologies presents a utopian moment for humankind, providing both the motive and the means to build a better future.
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.
This unified survey of the theory of adaptive filtering,
prediction, and control focuses on linear discrete-time systems and
explores the natural extensions to nonlinear systems. In keeping
with the importance of computers to practical applications, the
authors emphasize discrete-time systems. Their approach summarizes
the theoretical and practical aspects of a large class of adaptive
This textbook is aimed at newcomers to nonlinear dynamics and chaos, especially students taking a first course in the subject. The presentation stresses analytical methods, concrete examples, and geometric intuition. The theory is developed systematically, starting with first-order differential equations and their bifurcations, followed by phase plane analysis, limit cycles and their bifurcations, and culminating with the Lorenz equations, chaos, iterated maps, period doubling, renormalization, fractals, and strange attractors. A unique feature of the book is its emphasis on applications. These include mechanical vibrations, lasers, biological rhythms, superconducting circuits, insect outbreaks, chemical oscillators, genetic control systems, chaotic waterwheels, and even a technique for using chaos to send secret messages. In each case, the scientific background is explained at an elementary level and closely integrated with mathematical theory. In the twenty years since the first edition of this book appeared, the ideas and techniques of nonlinear dynamics and chaos have found application to such exciting fields as systems biology, evolutionary game theory, and socio-physics. This second edition includes new exercises on these cutting-edge developments, on topics as varied as curiosities of visual perception and the tumultuous love dynamics in Gone with the Wind.
This book takes Complexity Theory and applies it to medicine where it has previously made little ground. It provides new hypotheses for multiple common but misunderstood diseases. Doctors in particular will understand that many diseases have remained unsolved due to a linear approach to what are complex biological systems, and failure to understand and apply Complexity Theory. Therefore, many common conditions have no known cause and consequently treatments are either ineffectual or non-existant, when many of these diseases are in fact preventable. There is growing interest in non-linear science, dynamic systems, chaos and complexity theory. This trend has directly involved other sciences, including biology, but has been little touched on by medicine. Readers of this book will: * Understand the difference between Linear Science and Complexity Theory, and how medicine has failed to apply the latter. * Recognise the advantages of using this understanding to generate realistic hypotheses for cause of disease. * Read how hypotheses so generated have been formulated for a number of common diseases.
Kirk (emeritus, electrical engineering, San Jos State U.) introduces optimal control theory, which has as its objective the maximization of the return from, or the minimization of the cost of, the operation of physical, social, and economic processes. He concentrates on dynamic programming, Pontry
Only a few books stand as landmarks in social and scientific upheaval. Norbert Wiener's classic is one in that small company. Founder of the science of cybernetics--the study of the relationship between computers and the human nervous system--Wiener was widely misunderstood as one who advocated the automation of human life. As this book reveals, his vision was much more complex and interesting. He hoped that machines would release people from relentless and repetitive drudgery in order to achieve more creative pursuits. At the same time he realized the danger of dehumanizing and displacement. His book examines the implications of cybernetics for education, law, language, science, technology, as he anticipates the enormous impact--in effect, a third industrial revolution--that the computer has had on our lives.
Starting with a graph-theoretic framework for structural modeling of complex systems, this text presents results related to robust stabilization via decentralized state feedback. Subsequent chapters explore optimization, output feedback, the manipulative power of graphs, overlapping decompositions and the underlying inclusion principle, and reliability design. An appendix provides efficient graph algorithms. 1991 edition.
This book discusses the application of complex adaptive systems theory to the design and evaluation of patient-centered medical homes (PCMHs). The three defining goals of PCMHs are to spread patient-care roles among healthcare team members, focus on disease prevention and include the patient in the healthcare team. It explains why some PCMH pilots are highly successful while others do not show much benefit, covers specific sub-theories that allow for bracketing of different aspects of the clinic system and highlights strategies by which institutions can engage in this process. Inter professional Education in Patient-Centered Medical Homes is a valuable resource for faculty and managers of health professions teaching clinics, deans of medical and health professional schools and medical administrators.
This treatment of modern topics related to mathematical systems theory forms the proceedings of a workshop, Mathematical Systems Theory: From Behaviors to Nonlinear Control, held at the University of Groningen in July 2015. The workshop celebrated the work of Professors Arjan van der Schaft and Harry Trentelman, honouring their 60th Birthdays. The first volume of this two-volume work covers a variety of topics related to nonlinear and hybrid control systems. After giving a detailed account of the state of the art in the related topic, each chapter presents new results and discusses new directions. As such, this volume provides a broad picture of the theory of nonlinear and hybrid control systems for scientists and engineers with an interest in the interdisciplinary field of systems and control theory. The reader will benefit from the expert participants' ideas on exciting new approaches to control and system theory and their predictions of future directions for the subject that were discussed at the workshop.
The study of network theory is a highly interdisciplinary field, which has emerged as a major topic of interest in various disciplines ranging from physics and mathematics, to biology and sociology. This book promotes the diverse nature of the study of complex networks by balancing the needs of students from very different backgrounds. It references the most commonly used concepts in network theory, provides examples of their applications in solving practical problems, and clear indications on how to analyse their results. In the first part of the book, students and researchers will discover the quantitative and analytical tools necessary to work with complex networks, including the most basic concepts in network and graph theory, linear and matrix algebra, as well as the physical concepts most frequently used for studying networks. They will also find instruction on some key skills such as how to proof analytic results and how to manipulate empirical network data. The bulk of the text is focused on instructing readers on the most useful tools for modern practitioners of network theory. These include degree distributions, random networks, network fragments, centrality measures, clusters and communities, communicability, and local and global properties of networks. The combination of theory, example and method that are presented in this text, should ready the student to conduct their own analysis of networks with confidence and allow teachers to select appropriate examples and problems to teach this subject in the classroom.
A large-scale system is composed of several interconnected subsystems. For such a system it is often desired to have some form of decentralization in the control structure, since it is typically not realistic to assume that all output measurements can be transmitted to every local control station. Problems of this kind can appear in electric power systems, communication networks, large space structures, robotic systems, economic systems, and traffic networks, to name only a few. Typical large-scale control systems have several local control stations which observe only local outputs and control only local inputs. All controllers are involved, however, in the control operation of the overall system. The focus of this book is on the efficient control of interconnected systems, and it presents systems analysis and controller synthesis techniques using a variety of methods. A systematic study of multi-input, multi-output systems is carried out and illustrative examples are given to clarify the ideas.
Science world luminary John Brockman assembles twenty-five of the most important scientific minds, people who have been thinking about the field artificial intelligence for most of their careers, for an unparalleled round-table examination about mind, thinking, intelligence and what it means to be human.
More than sixty years ago, mathematician-philosopher Norbert Wiener published a book on the place of machines in society that ended with a warning: "we shall never receive the right answers to our questions unless we ask the right questions.... The hour is very late, and the choice of good and evil knocks at our door."
In the wake of advances in unsupervised, self-improving machine learning, a small but influential community of thinkers is considering Wiener's words again. In Possible Minds, John Brockman gathers their disparate visions of where AI might be taking us.
The fruit of the long history of Brockman's profound engagement with the most important scientific minds who have been thinking about AI--from Alison Gopnik and David Deutsch to Frank Wilczek and Stephen Wolfram--Possible Minds is an ideal introduction to the landscape of crucial issues AI presents. The collision between opposing perspectives is salutary and exhilarating; some of these figures, such as computer scientist Stuart Russell, Skype co-founder Jaan Tallinn, and physicist Max Tegmark, are deeply concerned with the threat of AI, including the existential one, while others, notably robotics entrepreneur Rodney Brooks, philosopher Daniel Dennett, and bestselling author Steven Pinker, have a very different view. Serious, searching and authoritative, Possible Minds lays out the intellectual landscape of one of the most important topics of our time.
"Energy Methods in Dynamics "is a textbook based on the lectures given by the first author at Ruhr University Bochum, Germany. Its aim is to help students acquire both a good grasp of the first principles from which the governing equations can be derived, and the adequate mathematical methods for their solving. Its distinctive features, as seen from the title, lie in the systematic and intensive use of Hamilton's variational principle and its generalizations for deriving the governing equations of conservative and dissipative mechanical systems, and also in providing the direct variational-asymptotic analysis, whenever available, of the energy and dissipation for the solution of these equations. It demonstrates that many well-known methods in dynamics like those of Lindstedt-Poincare, Bogoliubov-Mitropolsky, Kolmogorov-Arnold-Moser (KAM), Wentzel Kramers Brillouin (WKB), and Whitham are derivable from this variational-asymptotic analysis.
This second edition includes the solutions to all exercises as well as some new materials concerning amplitude and slope modulations of nonlinear dispersive waves."
Examines current and prospective challenges surrounding global challenges of education, energy, healthcare, security, and resilience This book discusses issues in large-scale systems in the United States and around the world. The authors examine the challenges of education, energy, healthcare, national security, and urban resilience. The book covers challenges in education including America's use of educational funds, standardized testing, and the use of classroom technology. On the topic of energy, this book examines debates on climate, the current and future developments of the nuclear power industry, the benefits and cost decline of natural gases, and the promise of renewable energy. The authors also discuss national security, focusing on the issues of nuclear weapons, terrorism and cyber security. Urban resilience is addressed in the context of natural threats such as hurricanes and floods. * Studies the usage of a globalized benchmark for both student and pedagogical performance * Covers topics such as surveillance, operational capabilities, movement of resources, and the pros and cons of globalization * Examines big data, evolving medical methodologies and effects on the medical educational curriculum, and the positive effects of electronic records in healthcare data Perspectives on Complex Global Challenges: Education, Energy Healthcare, Security, and Resilience serves as a reference for government officials, personnel in security, business executives and system engineers.
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