This book is an intellectually stimulating excursion into mathematical machines and structures capable for a universal computation. World top experts in computer science and mathematics overview exciting and intriguing topics of logical theory of monoids, geometry of Gauss word, philosophy of mathematics in computer science, asynchronous and parallel P-systems, decidability in cellular automata, splicing systems, reversible Turing machines, information flows in two-way finite automata, prime generators in automaton arrays, Grossone and Turing machines, automaton models of atomic lattices. The book is full of visually attractive examples of mathematical machines, open problems and challenges for future research. Those interested in the advancement of a theory of computation, philosophy of mathematics, future and emergent computing paradigms, architectures and implementations will find the book vital for their research and development.

Multilevel decision theory arises to resolve the contradiction between increasing requirements towards the process of design, synthesis, control and management of complex systems and the limitation of the power of technical, control, computer and other executive devices, which have to perform actions and to satisfy requirements in real time. This theory rises suggestions how to replace the centralised management of the system by hierarchical co-ordination of sub-processes. All sub-processes have lower dimensions, which support easier management and decision making. But the sub-processes are interconnected and they influence each other. Multilevel systems theory supports two main methodological tools: decomposition and co-ordination. Both have been developed, and implemented in practical applications concerning design, control and management of complex systems. In general, it is always beneficial to find the best or optimal solution in processes of system design, control and management. The real tendency towards the best (optimal) decision requires to present all activities in the form of a definition and then the solution of an appropriate optimization problem. Every optimization process needs the mathematical definition and solution of a well stated optimization problem. These problems belong to two classes: static optimization and dynamic optimization. Static optimization problems are solved applying methods of mathematical programming: conditional and unconditional optimization. Dynamic optimization problems are solved by methods of variation calculus: Euler Lagrange method; maximum principle; dynamical programming."

Using the O.D.D. (Overview, Design concepts, Detail) protocol, this title explores the role of agent-based modeling in predicting the feasibility of various approaches to sustainability. The chapters incorporated in this volume consist of real case studies to illustrate the utility of agent-based modeling and complexity theory in discovering a path to more efficient and sustainable lifestyles. The topics covered within include: households' attitudes toward recycling, designing decision trees for representing sustainable behaviors, negotiation-based parking allocation, auction-based traffic signal control, and others. This selection of papers will be of interest to social scientists who wish to learn more about agent-based modeling as well as experts in the field of agent-based modeling.

This book summarizes a network of interrelated ideas which I have developed, off and on, over the past eight or ten years. The underlying theme is the psychological interplay of order and chaos. Or, to put it another way, the interplay of deduction and induction. I will try to explain the relationship between logical, orderly, conscious, rule-following reason and fluid, self organizing, habit-governed, unconscious, chaos-infused intuition. My previous two books, The Structure of Intelligence and The Evolving Mind, briefly touched on this relationship. But these books were primarily concerned with other matters: SI with constructing a formal language for discussing mentality and its mechanization, and EM with exploring the role of evolution in thought. They danced around the edges of the order/chaos problem, without ever fully entering into it. My goal in writing this book was to go directly to the core of mental process, "where angels fear to tread" -- to tackle all the sticky issues which it is considered prudent to avoid: the nature of consciousness, the relation between mind and reality, the justification of belief systems, the connection between creativity and mental illness, .... All of these issues are dealt with here in a straightforward and unified way, using a combination of concepts from my previous work with ideas from chaos theory and complex systems science."

The book introduces novel algorithms for designing fault-tolerant control (FTC) systems using the behavioral system theoretic approach, and presents a demonstration of successful novel FTC mechanisms on several benchmark examples. The authors also discuss a new transient management scheme, which is an essential requirement for the implementation of active FTC systems, and two data-driven methodologies that are broadly classified as active FTC systems: the projection-based approach and the online-redesign approach. These algorithms do not require much a priori information about the plant in real-time, and in addition this novel implementation of active FTC systems circumvents various weaknesses induced by using a diagnostic module in real-time. The book provides graduate students taking masters and doctoral courses in mathematics, control, and electrical engineering an excellent stepping-stone for their research. It also appeals to practitioners interested to apply innovative fail-safe control techniques.

Structurally Constrained Controllers: Analysis and Synthesis studies the control of interconnected systems with a particular application in network, power systems, flight formations, etc. It introduces four important problems regarding the control of such systems and then proposes proper techniques for solving them.

This qualitative multi-case study of academic literacy is the first research to assume the premises of the Multiliteracies Project of the New London Group of literacy researchers. It takes a multimodal view of literacy, not limited to reading and writing, and sets about to uncover the Design (the flexible structuring of rules and principles) that students and teachers both follow and create in college courses. This Design takes the form of a game in which students channel content from sources, such as texts and lectures, to assessments of various kinds. Students are then rewarded in the form of grades to the extent that the content they display matches the criteria the professor sets up.

The students in this study had to determine which content would or would not match these criteria, which of six "types of information" (facts, concepts, connections, processes, principles, or metainformation, e.g., rhetorical patterns) were desired and how best to supply them. To move content from source to target they used four "operations." These include exposure (making themselves conscious of the information), extraction (a process of selecting information), manipulation (changing or synthesizing information), and display (showing the information). Greater awareness of this Design led to greater success. Pedagogical implications of this model include establishing a more realistic curricula for academic literacy programs and educating professors to better match grading criteria with learning goals.

This book is a self-contained elementary study for nonsmooth analysis and optimization, and their use in solution of nonsmooth optimal control problems. The first part of the book is concerned with nonsmooth differential calculus containing necessary tools for nonsmooth optimization. The second part is devoted to the methods of nonsmooth optimization and their development. A proximal bundle method for nonsmooth nonconvex optimization subject to nonsmooth constraints is constructed. In the last part nonsmooth optimization is applied to problems arising from optimal control of systems covered by partial differential equations. Several practical problems, like process control and optimal shape design problems are considered.

This book is a self-contained elementary study for nonsmooth analysis and optimization, and their use in solution of nonsmooth optimal control problems. The first part of the book is concerned with nonsmooth differential calculus containing necessary tools for nonsmooth optimization. The second part is devoted to the methods of nonsmooth optimization and their development. A proximal bundle method for nonsmooth nonconvex optimization subject to nonsmooth constraints is constructed. In the last part nonsmooth optimization is applied to problems arising from optimal control of systems covered by partial differential equations. Several practical problems, like process control and optimal shape design problems are considered.

This book provides recent theoretical developments in and practical applications of fault diagnosis and fault tolerant control for complex dynamical systems, including uncertain systems, linear and nonlinear systems. Combining adaptive control technique with other control methodologies, it investigates the problems of fault diagnosis and fault tolerant control for uncertain dynamic systems with or without time delay. As such, the book provides readers a solid understanding of fault diagnosis and fault tolerant control based on adaptive control technology. Given its depth and breadth, it is well suited for undergraduate and graduate courses on linear system theory, nonlinear system theory, fault diagnosis and fault tolerant control techniques. Further, it can be used as a reference source for academic research on fault diagnosis and fault tolerant control, and for postgraduates in the field of control theory and engineering.

This proceedings volume contains talks and poster presentations from the International Symposium "Self-Organization in Complex Systems: The Past, Present, and Future of Synergetics", which took place at Hanse-Wissenschaftskolleg, an Institute of Advanced Studies, in Delmenhorst, Germany, during the period November 13 - 16, 2012. The Symposium was organized in honour of Hermann Haken, who celebrated his 85th birthday in 2012. With his fundamental theory of Synergetics he had laid the mathematical-physical basis for describing and analyzing self-organization processes in a diversity of fields of research. The quest for common and universal principles of self-organization in complex systems was clearly covered by the wide range of interdisciplinary topics reported during the Symposium. These extended from complexity in classical systems and quantum systems over self-organisation in neuroscience even to the physics of finance. Moreover, by combining a historical view with a present status report the Symposium conveyed an impression of the allure and potency of this branch of research as well as its applicability in the future.

This book provides comprehensive coverage on a new direction in computational mathematics research: automatic search for formulas. Formulas must be sought in all areas of science and life: these are the laws of the universe, the macro and micro world, fundamental physics, engineering, weather and natural disasters forecasting; the search for new laws in economics, politics, sociology. Accumulating many years of experience in the development and application of numerical methods of symbolic regression to solving control problems, the authors offer new possibilities not only in the field of control automation, but also in the design of completely different optimal structures in many fields. For specialists in the field of control, Machine Learning Control by Symbolic Regression opens up a new promising direction of research and acquaints scientists with the methods of automatic construction of control systems.For specialists in the field of machine learning, the book opens up a new, much broader direction than neural networks: methods of symbolic regression. This book makes it easy to master this new area in machine learning and apply this approach everywhere neural networks are used. For mathematicians, the book opens up a new approach to the construction of numerical methods for obtaining analytical solutions to unsolvable problems; for example, numerical analytical solutions of algebraic equations, differential equations, non-trivial integrals, etc. For specialists in the field of artificial intelligence, the book offers a machine way to solve problems, framed in the form of analytical relationships.

This book provides an introduction to Swarm Robotics, which is the application of methods from swarm intelligence to robotics. It goes on to present methods that allow readers to understand how to design large-scale robot systems by going through many example scenarios on topics such as aggregation, coordinated motion (flocking), task allocation, self-assembly, collective construction, and environmental monitoring. The author explains the methodology behind building multiple, simple robots and how the complexity emerges from the multiple interactions between these robots such that they are able to solve difficult tasks. The book can be used as a short textbook for specialized courses or as an introduction to Swarm Robotics for graduate students, researchers, and professionals who want a concise introduction to the field.

The optimal estimation problems for linear dynamic systems, and in particular for systems with aftereffect, reduce to different variational problems. The type and complexity of these variational problems depend on the process model, the model of uncertainties, and the estimation performance criterion. A solution of a variational problem determines an optimal estimator. In addition, frequently the optimal algorithm for one noise model must operate under another, more complex assumption about noise. Hence, simplified algorithms must be used. It is important to evaluate the level of nonoptimality for the simplified algorithms. Since the original variational problems can be very difficult, the estimate of nonoptimality must be obtained without solving the original variational problem. In this book, guaranteed levels of nonoptimality for simplified estimation and control algorithms are constructed. To obtain these levels the duality theory for convex extremal problems is used. Audience: This book will be of interest to applied mathematicians, researchers and engineers who deal with estimation and control systems. The material, which requires a good knowledge of calculus, is also suitable for a two-semester graduate or postgraduate course.

The notion of information is multifaceted. According to the case, it is a simple signal or already knowledge. lt responds to codes and is inscribed into a social relationship. There are clearly many perspectives which the social sciences can take to analyse the notion of information. The economy cannot account for the majority of situations where, in the activities of production, consumption or exchange, the notion of information finds itself implied, although each school of thought has its own understanding of the notion of information. This book takes this observation as a starting point and goes on to clarify a contemporary debate on the economy of information which remains quite vague, making use of the ways in which different theoretical approaches deal with information. To seize the nature and scope of the transformations in our societies, a consequence of our new ways of handling, stocking and circulating information in the workings of the markets like Organisations, such a theoretical exercise seems useful. The organisation of the book results from this choice. The contributions gathered in one part deal with the role of information in the functioning of the markets, those featuring in another are more interested in the organisations. To favour an enriching cross-reading of approaches developed in the two sections already referred to, we have preceded these with a section gathering approaches (which are more transversal) developing different theories of information (according to perspectives which are, respectively, systematic, statistical or strategic).

The emergence of flow control as an attractive new field is owed to breakthroughs in MEMS (micro-electromechanical systems) and related technologies. The instrumentation of fluid flows on extremely short length and short time scales requires the practical tool of control algorithms with provable performance guarantees. Dedicated to this problem, Flow Control by Feedback, brings together controller design and fluid mechanics expertise in an exposition of the latest research results. Featuring: Exhaustive treatment of flow control core areas including stabilization and mixing control techniques; self-contained introductory sections on Navier-Stokes equations, linear and nonlinear control and sensors and MEMS to facilitate accessibility to this cross-disciplinary subject; a comprehensive survey of feedback algorithms for flow control that are currently available. In response to the intense interest in flow control, this volume will be an essential addition to the library of researchers and graduate students in control theory, fluid mechanics, mathematics and physics. Content structure is ideal for instruction on flow control modules or as supplementary reading on fluid dynamics and infinite dimensional systems courses.

Intelligence results from the interaction of the brain, body and environment. The question addressed in this book is, can we measure the contribution of the body and its' interaction with the environment? To answer this, we first present a comprehensive overview of the various ways in which a body reduces the amount of computation that the brain has to perform to solve a task. This chapter will broaden your understanding of how important inconspicuously appearing physical processes and physical properties of the body are with respect to our cognitive abilities. This form of contribution to intelligence is called Morphological Intelligence. The main contribution of this book to the field is a detailed discussion of how Morphological Intelligence can be measured from observations alone. The required mathematical framework is provided so that readers unfamiliar with information theory will be able to understand and apply the measures. Case studies from biomechanics and soft robotics illustrate how the presented quantifications can, for example, be used to measure the contribution of muscle physics to jumping and optimise the shape of a soft robotic hand. To summarise, this monograph presents various examples of how the physical properties of the body and the body's interaction with the environment contribute to intelligence. Furthermore, it treats theoretical and practical aspects of Morphological Intelligence and demonstrates the value in two case studies.

This book develops an innovative system, in the form of an "app", that harnesses the power of the internet to predict which sorts of people will prefer which policy in ANY planning situation. It chronicles the accumulated research wisdom behind the system's reasoning, along with several less successful approaches to policy making that have been found wanting in the past - including the myth, usually peddled by strategic planners, that it is possible to find a "best" plan which optimally satisfies everybody. The book lays out an entirely new kind of Planning Support System (PSS). It will facilitate decision-making that is far more community-sensitive than previously, and it will drastically improve the performance of anyone who needs to plan within socially-sensitive contexts - which is all of us. A standout feature of the system is its commitment to "scientific rigour", as shown by its predicted plan scores always being graphically presented within error margins so that true statistical significance is instantly observable. Moreover, the probabilities that its predictions are correct are always shown - a refreshing change from most, if not all other Decision Support Systems (DSS) that simply expect users to accept their outputs on faith alone.

Introduction to Intelligent Simulation of Complex Discrete Systems and Processes: RAO Language focuses on a unique approach in modeling and simulation of complex systems. In this volume are considered features of complex systems and processes, their mathematical description, and modeling. Theoretical foundations of the RAO (Resource-Action-Operation) language as well as its syntax and utilisation are given. Examples of simulation models of different complexity levels, related to different fields, are also presented. The RAO intelligent modeling system, introduced and described in Introduction to Intelligent Simulation of Complex Discrete Systems and Processes is unique because: (1) it makes simulation modeling universal for the classes of systems and processes modeled; (2) it is simple to modify the models; and (3) it has the capacity to model complex control systems together with the object controlled (including simulation modeling for on-line control). The RAO tool allows the user to use a language very similar to his professional language and rids him of intermediary, supplementary description of the system modeled. In fifteen chapters this volume provides an overview of general modeling trends, and hence serves the research community in guiding their modeling methods; intelligent simulation modeling is introduced to solve complex systems and processes.

This book examines the relationship between communication and organizational structure. It demonstrates that organizational structure must align itself with communication structure for effective performance. A detailed table of the communication process is used to examine a range of organization structures including scientific management, bureaucracy, functional integration, management by objectives, strategic alignment, quality management, and self-managing teams. The examination concludes that the structure required for the 21st century will put into effect Follett's principle of functional integration, but associate with it techniques such as strategic alignment and quality management. Functional integration requires mutual negotiation of meaning and relatedness built on integration of the individual, the group, and the organization. The development of controlled cooperation resulting from mutual negotiation and integration will make formidable demands on managerial competence. This book provides readers with a strategy for organizing a workforce with expectations of personal fulfillment from work, in a climate of intense international competition.

This book presents applications of Newton-like and other similar methods to solve abstract functional equations involving fractional derivatives. It focuses on Banach space-valued functions of a real domain - studied for the first time in the literature. Various issues related to the modeling and analysis of fractional order systems continue to grow in popularity, and the book provides a deeper and more formal analysis of selected issues that are relevant to many areas - including decision-making, complex processes, systems modeling and control - and deeply embedded in the fields of engineering, computer science, physics, economics, and the social and life sciences. The book offers a valuable resource for researchers and graduate students, and can also be used as a textbook for seminars on the above-mentioned subjects. All chapters are self-contained and can be read independently. Further, each chapter includes an extensive list of references.

The book addresses the relationship between knowledge, complexity and innovation systems. It integrates research findings from a broad area including economics, business studies, management studies, geography, mathematics and science & technology contributions from a wide range group of international experts. In particular, it offers insights about knowledge creation and spillovers, innovation and learning systems, innovation diffusion processes and innovation policies.The contributions provide an excellent coverage of current conceptual and theoretical developments and valuable insights from both empirical and conceptual work. The reader gets an overview about the state of the art of the role of innovation systems and knowledge creation and diffusion in geographical space.

Codes, Curves, and Signals: Common Threads in Communications is a collection of seventeen contributions from leading researchers in communications. The book provides a representative cross-section of cutting edge contemporary research in the fields of algebraic curves and the associated decoding algorithms, the use of signal processing techniques in coding theory, and the application of information-theoretic methods in communications and signal processing. The book is organized into three parts: Curves and Codes, Codes and Signals, and Signals and Information. Codes, Curves, and Signals: Common Threads in Communications is a tribute to the broad and profound influence of Richard E. Blahut on the fields of algebraic coding, information theory, and digital signal processing. All the contributors have individually and collectively dedicated their work to R. E. Blahut. Codes, Curves, and Signals: Common Threads in Communications is an excellent reference for researchers and professionals.