Complexity Theory and the Management of Networks


Book Description

Annotation This proceedings volume presents a multi-disciplinary analysis of modern businesses as complex systems and some managerial implications of managing complex networks in the knowledge economy. It discusses the impact of major forces that are altering today's business landscape, such as sweeping technological changes, unbundling of integrated structures, growing interdependence between once-independent sectors and increased unpredictability of strategy outcomes. The result has been and will increasingly be the dominion of complex interconnected networks in business. One of the challenges facing today's management is to develop theories and practices that address the dynamics of business networks. Complexity theory has much to contribute to this purpose. Thus, this volume focuses on exploring the emerging patterns of order and discussing the new management practices suitable to the network economy.




Complexity Theory And The Management Of Networks: Proceedings Of The Workshop On Organisational Networks As Distributed Systems Of Knowledge


Book Description

One of the challenges facing today's management is to develop theories and practices that address the dynamics of business networks. Complexity theory has much to contribute to this purpose. Thus, this volume focuses on exploring the emerging patterns of order and discussing the new management practices suitable to the network economy. Its presents a multidisciplinary analysis of modern businesses as complex systems and some managerial implications of managing complex networks in the knowledge economy. It discusses the impact of major forces that are altering today's business landscape, such as sweeping technological changes, unbundling of integrated structures, growing interdependence between once-independent sectors and increased unpredictability of strategy outcomes. The result has been and will increasingly be the dominion of complex interconnected networks in business.Some of the distinguished contributors include Bill McKelvey from UCLA, Richard Hall from the University of Durham and John L Casti from the University of Southern California.




Circuit Complexity and Neural Networks


Book Description

Neural networks usually work adequately on small problems but can run into trouble when they are scaled up to problems involving large amounts of input data. Circuit Complexity and Neural Networks addresses the important question of how well neural networks scale - that is, how fast the computation time and number of neurons grow as the problem size increases. It surveys recent research in circuit complexity (a robust branch of theoretical computer science) and applies this work to a theoretical understanding of the problem of scalability. Most research in neural networks focuses on learning, yet it is important to understand the physical limitations of the network before the resources needed to solve a certain problem can be calculated. One of the aims of this book is to compare the complexity of neural networks and the complexity of conventional computers, looking at the computational ability and resources (neurons and time) that are a necessary part of the foundations of neural network learning. Circuit Complexity and Neural Networks contains a significant amount of background material on conventional complexity theory that will enable neural network scientists to learn about how complexity theory applies to their discipline, and allow complexity theorists to see how their discipline applies to neural networks.




Complexity Theory for a Sustainable Future


Book Description

Complexity theory illuminates the many interactions between natural and social systems, providing a better understanding of the general principles that can help solve some of today's most pressing environmental issues. Complexity theory was developed from key ideas in economics, physics, biology, and the social sciences and contributes to important new concepts for approaching issues of environmental sustainability such as resilience, scaling, and networks. Complexity Theory for a Sustainable Future is a hands-on treatment of this exciting new body of work and its applications, bridging the gap between theoretical and applied perspectives in the management of complex adaptive systems. Focusing primarily on natural resource management and community-based conservation, the book features contributions by leading scholars in the field, many of whom are among the leaders of the Resilience Alliance. Theoreticians will find a valuable synthesis of new ideas on resilience, sustainability, asymmetries, information processing, scaling, and networks. Managers and policymakers will benefit from the application of these ideas to practical approaches and empirical studies linked to social-ecological systems. Chapters present new twists on such existing approaches as scenario planning, scaling analyses, and adaptive management, and the book concludes with recommendations on how to manage natural resources, how to involve stakeholders in the dynamics of a system, and how to explain the difficult topic of scale. A vital reference for an emerging discipline, this volume provides a clearer understanding of the conditions required for systems self-organization, since the capacity of any system to self-organize is crucial for its sustainability over time.




Complexity Theory and Network Centric Warfare


Book Description

A report by the Dept. of Defense¿s Command and Control Research Program. Contents: (1) Complexity in Natural and Economic Systems; (2) Concepts for Warfare from Complexity Theory; (3) Evidence for Complex Emergent Behavior in Historical Data; (4) Mathematical Modeling of Complexity, Knowledge, and Conflict; (5) An Extended Example of the Dynamics of Local Collaboration and Clustering, and Some Final Thoughts. Appendix: Optimal Control with a Unique Control Solution. Tables and figures.




Chaos and Complexity Theory for Management: Nonlinear Dynamics


Book Description

Although chaos theory refers to the existence between seemingly random events, it has been gaining the attention of science, technology and managements fields. The shift from traditional procedures to the dynamics of chaos and complexity theory has resulted in a new element of complexity thinking, allowing for a greater capability for analyzing and understanding key business processes. Chaos and Complexity Theory for Management: Nonlinear Dynamics explores chaos and complexity theory and its relationship with the understanding of natural chaos in the business environment. Utilizing these theories aids in comprehending the development of businesses as a complex adaptive system.




Neural Network Design and the Complexity of Learning


Book Description

Using the tools of complexity theory, Stephen Judd develops a formal description of associative learning in connectionist networks. He rigorously exposes the computational difficulties in training neural networks and explores how certain design principles will or will not make the problems easier.Judd looks beyond the scope of any one particular learning rule, at a level above the details of neurons. There he finds new issues that arise when great numbers of neurons are employed and he offers fresh insights into design principles that could guide the construction of artificial and biological neural networks.The first part of the book describes the motivations and goals of the study and relates them to current scientific theory. It provides an overview of the major ideas, formulates the general learning problem with an eye to the computational complexity of the task, reviews current theory on learning, relates the book's model of learning to other models outside the connectionist paradigm, and sets out to examine scale-up issues in connectionist learning.Later chapters prove the intractability of the general case of memorizing in networks, elaborate on implications of this intractability and point out several corollaries applying to various special subcases. Judd refines the distinctive characteristics of the difficulties with families of shallow networks, addresses concerns about the ability of neural networks to generalize, and summarizes the results, implications, and possible extensions of the work. Neural Network Design and the Complexity of Learning is included in the Network Modeling and Connectionism series edited by Jeffrey Elman.




Complexity Theory and the Social Sciences


Book Description

Chaos and complexity are the new buzz words in both science and contemporary society. The ideas they represent have enormous implications for the way we understand and engage with the world. Complexity Theory and the Social Sciences introduces students to the central ideas which surround the chaos/complexity theories. It discusses key concepts before using them as a way of investigating the nature of social research. By applying them to such familiar topics as urban studies, education and health, David Byrne allows readers new to the subject to appreciate the contribution which complexity theory can make to social research and to illuminating the crucial social issues of our day.




Successful Program Management


Book Description

Complexity theory is a great, untapped resource in the field of management. Experts agree that it can be a powerful tool for managing complex and virtual programs, but there is little material available to guide program managers on how to use complexity theory to communicate and lead effectively.Filling this void, Successful Program Management: Com




School Leadership and Complexity Theory


Book Description

This book moves forward the agenda significantly. It enables educational leadership and management discourse to be informed by the latest views that are becoming well established in business and organisational literature in practice.