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A robotics genius, Edmond West has developed a plan to create the world's first Artificial Intelligence truly indistinguishable from a human being. His Bots will eradicate global slavery and allow humanity to channel its darkest impulses safely, harming only these soulless machines. His greatest success, however, may also be his undoing. He's finally created the perfect humanoid robot; perfectly intuitive, perfectly emotive… and perfectly unpredictable. Emergent Behavior is Book #1 from Bots, an EPIC Press series. Some titles may contain explicit content and/or language.
A comprehensive text that reviews the methods and technologies that explore emergent behavior in complex systems engineering in multidisciplinary fields In Emergent Behavior in Complex Systems Engineering, the authors present the theoretical considerations and the tools required to enable the study of emergent behaviors in manmade systems. Information Technology is key to today’s modern world. Scientific theories introduced in the last five decades can now be realized with the latest computational infrastructure. Modeling and simulation, along with Big Data technologies are at the forefront of such exploration and investigation. The text offers a number of simulation-based methods, technologies, and approaches that are designed to encourage the reader to incorporate simulation technologies to further their understanding of emergent behavior in complex systems. The authors present a resource for those designing, developing, managing, operating, and maintaining systems, including system of systems. The guide is designed to help better detect, analyse, understand, and manage the emergent behaviour inherent in complex systems engineering in order to reap the benefits of innovations and avoid the dangers of unforeseen consequences. This vital resource: Presents coverage of a wide range of simulation technologies Explores the subject of emergence through the lens of Modeling and Simulation (M&S) Offers contributions from authors at the forefront of various related disciplines such as philosophy, science, engineering, sociology, and economics Contains information on the next generation of complex systems engineering Written for researchers, lecturers, and students, Emergent Behavior in Complex Systems Engineering provides an overview of the current discussions on complexity and emergence, and shows how systems engineering methods in general and simulation methods in particular can help in gaining new insights in complex systems engineering.
In the tradition of Octavia Butler, here is radical self-help, society-help, and planet-help to shape the futures we want. Change is constant. The world, our bodies, and our minds are in a constant state of flux. They are a stream of ever-mutating, emergent patterns. Rather than steel ourselves against such change, Emergent Strategy teaches us to map and assess the swirling structures and to read them as they happen, all the better to shape that which ultimately shapes us, personally and politically. A resolutely materialist spirituality based equally on science and science fiction: a wild feminist and afro-futurist ride! adrienne maree brown, co-editor of Octavia’s Brood: Science Fiction from Social Justice Movements, is a social justice facilitator, healer, and doula living in Detroit.
Emergence and complexity refer to the appearance of higher-level properties and behaviours of a system that obviously comes from the collective dynamics of that system's components. These properties are not directly deducible from the lower-level motion of that system. Emergent properties are properties of the "whole'' that are not possessed by any of the individual parts making up that whole. Such phenomena exist in various domains and can be described, using complexity concepts and thematic knowledges. This book highlights complexity modelling through dynamical or behavioral systems. The pluridisciplinary purposes, developed along the chapters, are able to design links between a wide-range of fundamental and applicative Sciences. Developing such links - instead of focusing on specific and narrow researches - is characteristic of the Science of Complexity that we try to promote by this contribution.
"This book compiles real-world case studies on discovering, understanding and engineering emergent behaviors in a computational environment across multiple application domains such as wargaming, biology, IoT, disaster management and space architecting. All the application domains are described through an undercurrent of System of Systems (SoS) engineering in conjunction with theoretical foundations required for engineering a Modeling and Simulation SoS capable of displaying valid emergent behavior. An excellent read and state-of-the-art in M&S of emergent behavior in complex systems!" --Dr. Saurabh Mittal, Department Chief Scientist, The MITRE Corporation This book is the of its kind to address real-world applications of the phenomenon of emergent behavior in real-world system of systems. It launches from the foundation of theory and basic understanding of the subject of emergent behavior as found in system of systems applications. It includes real-world examples where emergent behavior is manifested. Each chapter addresses the following major points, which are exploratory in nature: the physical results of the presence of emergent behavior; the implications for the existence of emergent behavior; the manifestation of emergent behavior; and methods to either control emergent behavior assuming its effects are negative in nature, or capitalize on emergent behavior given its effects are positive in nature.
This book addresses problems in the modeling, detection, and control of emergent behaviors and task coordination in multiagent systems. It presents a unified solution to such problems in terms of distributed estimation, distributed control, and optimization of interaction topologies and dynamics. Four aspects of the technical solutions in the book are presented: First, the impact of interaction dynamics on the convergence conditions related to interaction topologies is discussed, utilizing a discontinuous cooperative control algorithm of updated design. Second, distributed least-squares and Kalman filtering algorithms for agents with limited interactions are elaborated upon. Third, a general framework of distributed nonlinear control is established, and distributed adaptive control for nonlinear systems with more general uncertainties is presented. Based on the proposed framework, a distributed nonlinear controller is designed to deal with task coordination of robotic systems with nonholonomic constraints. Finally, the problem of optimal multiagent task coordination is addressed and solutions based on approximate dynamic programming and approximate distributed gradient estimation are presented. Emergent Behavior Detection and Task Coordination for Multiagent Systems is of interest to practicing engineers in areas such as robotics and cyber-physical systems, researchers in the field of systems, controls, and robotics, and senior undergraduate and graduate students.
In the tradition of Being Digital and The Tipping Point, Steven Johnson, acclaimed as a "cultural critic with a poet's heart" (The Village Voice), takes readers on an eye-opening journey through emergence theory and its applications. A NEW YORK TIMES NOTABLE BOOK A VOICE LITERARY SUPPLEMENT TOP 25 FAVORITE BOOKS OF THE YEAR AN ESQUIRE MAGAZINE BEST BOOK OF THE YEAR Explaining why the whole is sometimes smarter than the sum of its parts, Johnson presents surprising examples of feedback, self-organization, and adaptive learning. How does a lively neighborhood evolve out of a disconnected group of shopkeepers, bartenders, and real estate developers? How does a media event take on a life of its own? How will new software programs create an intelligent World Wide Web? In the coming years, the power of self-organization -- coupled with the connective technology of the Internet -- will usher in a revolution every bit as significant as the introduction of electricity. Provocative and engaging, Emergence puts you on the front lines of this exciting upheaval in science and thought.
We are confronted with emergent systems everywhere and Holland shows how a theory of emergence can predict many complex behaviours in art and science. This book will appeal to scientists and anyone interested in scientific theory.
The concept of emergence has seen a significant resurgence in philosophy and the sciences, yet debates regarding emergentist and reductionist visions of the natural world continue to be hampered by imprecision or ambiguity. Emergent phenomena are said to arise out of and be sustained by more basic phenomena, while at the same time exerting a "top-down" control upon those very sustaining processes. To some critics, this has the air of magic, as it seems to suggest a kind of circular causality. Other critics deem the concept of emergence to be objectionably anti-naturalistic. Objections such as these have led many thinkers to construe emergent phenomena instead as coarse-grained patterns in the world that, while calling for distinctive concepts, do not "disrupt" the ordinary dynamics of the finer-grained (more fundamental) levels. Yet, reconciling emergence with a (presumed) pervasive causal continuity at the fundamental level can seem to deflate emergence of its initially profound significance. This basic problematic is mirrored by similar controversy over how best to characterize the opposite systematizing impulse, most commonly given an equally evocative but vague term, "reductionism." The original essays in this volume help to clarify the alternatives: inadequacies in some older formulations and arguments are exposed and new lines of argument on behalf the two visions are advanced.
Human-Machine Shared Contexts considers the foundations, metrics, and applications of human-machine systems. Editors and authors debate whether machines, humans, and systems should speak only to each other, only to humans, or to both and how. The book establishes the meaning and operation of “shared contexts between humans and machines; it also explores how human-machine systems affect targeted audiences (researchers, machines, robots, users) and society, as well as future ecosystems composed of humans and machines. This book explores how user interventions may improve the context for autonomous machines operating in unfamiliar environments or when experiencing unanticipated events; how autonomous machines can be taught to explain contexts by reasoning, inferences, or causality, and decisions to humans relying on intuition; and for mutual context, how these machines may interdependently affect human awareness, teams and society, and how these "machines" may be affected in turn. In short, can context be mutually constructed and shared between machines and humans? The editors are interested in whether shared context follows when machines begin to think, or, like humans, develop subjective states that allow them to monitor and report on their interpretations of reality, forcing scientists to rethink the general model of human social behavior. If dependence on machine learning continues or grows, the public will also be interested in what happens to context shared by users, teams of humans and machines, or society when these machines malfunction. As scientists and engineers "think through this change in human terms," the ultimate goal is for AI to advance the performance of autonomous machines and teams of humans and machines for the betterment of society wherever these machines interact with humans or other machines. This book will be essential reading for professional, industrial, and military computer scientists and engineers; machine learning (ML) and artificial intelligence (AI) scientists and engineers, especially those engaged in research on autonomy, computational context, and human-machine shared contexts; advanced robotics scientists and engineers; scientists working with or interested in data issues for autonomous systems such as with the use of scarce data for training and operations with and without user interventions; social psychologists, scientists and physical research scientists pursuing models of shared context; modelers of the internet of things (IOT); systems of systems scientists and engineers and economists; scientists and engineers working with agent-based models (ABMs); policy specialists concerned with the impact of AI and ML on society and civilization; network scientists and engineers; applied mathematicians (e.g., holon theory, information theory); computational linguists; and blockchain scientists and engineers. Discusses the foundations, metrics, and applications of human-machine systems Considers advances and challenges in the performance of autonomous machines and teams of humans Debates theoretical human-machine ecosystem models and what happens when machines malfunction