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Adaptive Networks

Adaptive Networks PDF Author: Thilo Gross
Publisher: Springer Science & Business Media
ISBN: 3642012841
Category : Science
Languages : en
Pages : 340

Book Description
Adding one and one makes two, usually. But sometimes things add up to more than the sum of their parts. This observation, now frequently expressed in the maxim “more is different”, is one of the characteristic features of complex systems and, in particular, complex networks. Along with their ubiquity in real world systems, the ability of networks to exhibit emergent dynamics, once they reach a certain size, has rendered them highly attractive targets for research. The resulting network hype has made the word “network” one of the most in uential buzzwords seen in almost every corner of science, from physics and biology to economy and social sciences. The theme of “more is different” appears in a different way in the present v- ume, from the viewpoint of what we call “adaptive networks.” Adaptive networks uniquely combine dynamics on a network with dynamical adaptive changes of the underlying network topology, and thus they link classes of mechanisms that were previously studied in isolation. Here adding one and one certainly does not make two, but gives rise to a number of new phenomena, including highly robust se- organization of topology and dynamics and other remarkably rich dynamical beh- iors.

Adaptive Networks

Adaptive Networks PDF Author: Thilo Gross
Publisher: Springer Science & Business Media
ISBN: 3642012841
Category : Science
Languages : en
Pages : 340

Book Description
Adding one and one makes two, usually. But sometimes things add up to more than the sum of their parts. This observation, now frequently expressed in the maxim “more is different”, is one of the characteristic features of complex systems and, in particular, complex networks. Along with their ubiquity in real world systems, the ability of networks to exhibit emergent dynamics, once they reach a certain size, has rendered them highly attractive targets for research. The resulting network hype has made the word “network” one of the most in uential buzzwords seen in almost every corner of science, from physics and biology to economy and social sciences. The theme of “more is different” appears in a different way in the present v- ume, from the viewpoint of what we call “adaptive networks.” Adaptive networks uniquely combine dynamics on a network with dynamical adaptive changes of the underlying network topology, and thus they link classes of mechanisms that were previously studied in isolation. Here adding one and one certainly does not make two, but gives rise to a number of new phenomena, including highly robust se- organization of topology and dynamics and other remarkably rich dynamical beh- iors.

Adaptive Networks

Adaptive Networks PDF Author: Sibout G. Nooteboom
Publisher: Eburon Uitgeverij B.V.
ISBN: 9059721470
Category : Public-private sector cooperation
Languages : en
Pages : 254

Book Description
Public and private managers who are looking for sustainable development have to implement innovative solutions in a complex field of action. Joint action is needed, but the existing power networks within and between public and private domains tend to frustrate joint innovations. This book analyzes how public and private managers deal with energy transitions by creating innovative networks capable of co-ordinated action. A case study shows how separated power networks in the field of mobility, energy and environment, which are spread over the public and private world as well as civil society, are becoming more interconnected

Self-Organization in Continuous Adaptive Networks

Self-Organization in Continuous Adaptive Networks PDF Author: Anne-Ly Do
Publisher: CRC Press
ISBN: 1000794393
Category : Computers
Languages : en
Pages : 110

Book Description
In the last years, adaptive networks have been discovered simultaneously in different fields as a universal framework for the study of self-organization phenomena. Understanding the mechanisms behind these phenomena is hoped to bring forward not only empirical disciplines such as biology, sociology, ecology, and economy, but also engineering disciplines seeking to employ controlled emergence in future technologies. This volume presents new analytical approaches, which combine tools from dynamical systems theory and statistical physics with tools from graph theory to address the principles behind adaptive self-organization. It is the first class of approaches that is applicable to continuous networks. The volume discusses the mechanisms behind three emergent phenomena that are prominently discussed in the context of biological and social sciences:• synchronization,• spontaneous diversification, and• self-organized criticality.Self-organization in continuous adaptive networks contains extended research papers. It can serve as both, a review of recent results on adaptive self-organization as well as a tutorial of new analytical methodsSelf-organization in continuous adaptive networks is ideal for academic staff and master/research students in complexity and network sciences, in engineering, physics and maths.

Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models

Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models PDF Author: Jan Treur
Publisher: Springer Nature
ISBN: 3030314456
Category : Technology & Engineering
Languages : en
Pages : 412

Book Description
This book addresses the challenging topic of modeling adaptive networks, which often manifest inherently complex behavior. Networks by themselves can usually be modeled using a neat, declarative, and conceptually transparent Network-Oriented Modeling approach. In contrast, adaptive networks are networks that change their structure; for example, connections in Mental Networks usually change due to learning, while connections in Social Networks change due to various social dynamics. For adaptive networks, separate procedural specifications are often added for the adaptation process. Accordingly, modelers have to deal with a less transparent, hybrid specification, part of which is often more at a programming level than at a modeling level. This book presents an overall Network-Oriented Modeling approach that makes designing adaptive network models much easier, because the adaptation process, too, is modeled in a neat, declarative, and conceptually transparent Network-Oriented Modeling manner, like the network itself. Thanks to this approach, no procedural, algorithmic, or programming skills are needed to design complex adaptive network models. A dedicated software environment is available to run these adaptive network models from their high-level specifications. Moreover, because adaptive networks are described in a network format as well, the approach can simply be applied iteratively, so that higher-order adaptive networks in which network adaptation itself is adaptive (second-order adaptation), too can be modeled just as easily. For example, this can be applied to model metaplasticity in cognitive neuroscience, or second-order adaptation in biological and social contexts. The book illustrates the usefulness of this approach via numerous examples of complex (higher-order) adaptive network models for a wide variety of biological, mental, and social processes. The book is suitable for multidisciplinary Master’s and Ph.D. students without assuming much prior knowledge, although also some elementary mathematical analysis is involved. Given the detailed information provided, it can be used as an introduction to Network-Oriented Modeling for adaptive networks. The material is ideally suited for teaching undergraduate and graduate students with multidisciplinary backgrounds or interests. Lecturers will find additional material such as slides, assignments, and software.

Learning and Computational Neuroscience

Learning and Computational Neuroscience PDF Author: Michael R. Gabriel
Publisher: Mit Press
ISBN: 9780262071024
Category : Apprentissage
Languages : en
Pages : 613

Book Description
"Learning and Computational Neuroscience" presents recent advances in understanding the brain processes underlying learning and memory, including neural systems analyses of dynamic circuit interactions in the brain and computational models capable of describing simple forms of learning and performance. Its principal aim is to show how each approach is related to and benefits the other, providing a powerful strategy for understanding cognitive processes.Michael Gabriel is Professor of Psychology at the University of Illinois. John Moore is Professor of Psychology and Associate Professor of Computer and Information Science at the University of Massachusetts at Amherst.Contributors: Michael Gabriel and John Moore. Joseph E. LeDoux, Bruce S. Kapp, Amy Wilson, Jeffrey P. Pascoe, William Supple, Paul J. Whalen, Norman W. Weinberger, John H. Ashe, Raju Metherate, David M. Diamond, Jon S. Bakin, J. Michael Cassady. Nestor A. Schmajuk. Malcolm W. Brown. Theodore W. Berger, German Barri onuevo, Steven P. Levitan, Donald N. Krieger, Robert J. H. Sclabassi. Neil E. Berthier, Diana E. J. Blazis. E. James Kehoe. John E. Desmond. A. Harry Klopf, James S. Morgan. Richard S. Sutton, Andrew G. Barto. Christopher J. C. H. Watkins.

Evolution of Cognitive Networks and Self-Adaptive Communication Systems

Evolution of Cognitive Networks and Self-Adaptive Communication Systems PDF Author: Lagkas, Thomas D.
Publisher: IGI Global
ISBN: 1466641908
Category : Computers
Languages : en
Pages : 438

Book Description
Cognitive networks can be crucial for the evolution of future communication systems; however, current trends have indicated major movement in other relevant fields towards the integration of different techniques for the realization of self-aware and self-adaptive communication systems. Evolution of Cognitive Networks and Self-Adaptive Communication Systems overviews innovative technologies combined for the formation of self-aware, self-adaptive, and self-organizing networks. By aiming to inform the research community and the related industry of solutions for cognitive networks, this book is essential for researchers, instructors, and professionals interested in clarifying the latest trends resulting in a unified realization for cognitive networking and communication systems.

Active and Programmable Networks for Adaptive Architectures and Services

Active and Programmable Networks for Adaptive Architectures and Services PDF Author: Syed Asad Hussain
Publisher: CRC Press
ISBN: 1420013653
Category : Technology & Engineering
Languages : en
Pages : 352

Book Description
Most conventional networks are passive, with only basic traffic monitoring, management, routing, and congestion control. At best, they can be called reactive. Deploying new functions and integrating new standards into these architectures is difficult due to the rigid embedding of software and hardware into the network components. Active and Programmable Networks for Adaptive Architectures and Services introduces a new generation of network technologies and architecture that allows the creation, customization, and management of new services and applications deployed dynamically into network nodes. Following a brief introduction and historical overview, the author outlines the architecture of active and programmable networks, discusses the enabling technologies for network programmability in detail, and introduces several paradigms and prototypes. He then explores packet scheduling, management, routing, and security and examines active wireless and mobile networks. The final chapter presents several real-world examples of currently deployed active and programmable networks. Several tables present information on different schemes and architectures, allowing easy comparison among a range of networking options. Placing the new paradigm in contrast with concepts such as TCP/IP and OSI, Active and Programmable Networks for Adaptive Architectures and Services makes it easy to see how these new technologies can help you build more flexible and adaptive networks that can seamlessly integrate new functions.

Reviews of Nonlinear Dynamics and Complexity

Reviews of Nonlinear Dynamics and Complexity PDF Author: Heinz Georg Schuster
Publisher: John Wiley & Sons
ISBN: 3527628010
Category : Science
Languages : en
Pages : 258

Book Description
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.

Adaptive Pattern Recognition and Neural Networks

Adaptive Pattern Recognition and Neural Networks PDF Author: Yoh-Han Pao
Publisher: Addison Wesley Publishing Company
ISBN:
Category : Computers
Languages : en
Pages : 344

Book Description
A coherent introduction to the basic concepts of pattern recognition, incorporating recent advances from AI, neurobiology, engineering, and other disciplines. Treats specifically the implementation of adaptive pattern recognition to neural networks. Annotation copyright Book News, Inc. Portland, Or.

Handbook on Biological Networks

Handbook on Biological Networks PDF Author: Stefano Boccaletti
Publisher: World Scientific
ISBN: 9812838805
Category : Mathematics
Languages : en
Pages : 465

Book Description
Networked systems are all around us. The accumulated evidence of systems as complex as a cell cannot be fully understood by studying only their isolated constituents, giving rise to a new area of interest in research OCo the study of complex networks . In a broad sense, biological networks have been one of the most studied networks, and the field has benefited from many important contributions. By understanding and modeling the structure of a biological network, a better perception of its dynamical and functional behavior is to be expected. This unique book compiles the most relevant results and novel insights provided by network theory in the biological sciences, ranging from the structure and dynamics of the brain to cellular and protein networks and to population-level biology. Sample Chapter(s). Chapter 1: Introduction (61 KB). Contents: Networks at the Cellular Level: The Structural Network Properties of Biological Systems (M Brilli & P Li); Dynamics of Multicellular Synthetic Gene Networks (E Ullner et al.); Boolean Networks in Inference and Dynamic Modeling of Biological Systems at the Molecular and Physiological Level (J Thakar & R Albert); Complexity of Boolean Dynamics in Simple Models of Signaling Networks and in Real Genetic Networks (A D az-Guilera & R ulvarez-Buylla); Geometry and Topology of Folding Landscapes (L Bongini & L Casetti); Elastic Network Models for Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses (T R Lezon et al.); Metabolic Networks (M C Palumbo et al.); Brain Networks: The Human Brain Network (O Sporns); Brain Network Analysis from High-Resolution EEG Signals (F De Vico Fallani & F Babiloni); An Optimization Approach to the Structure of the Neuronal layout of C elegans (A Arenas et al.); Cultured Neuronal Networks Express Complex Patterns of Activity and Morphological Memory (N Raichman et al.); Synchrony and Precise Timing in Complex Neural Networks (R-M Memmesheimer & M Timme); Networks at the Individual and Population Levels: Ideas for Moving Beyond Structure to Dynamics of Ecological Networks (D B Stouffer et al.); Evolutionary Models for Simple Biosystems (F Bagnoli); Evolution of Cooperation in Adaptive Social Networks (S Van Segbroeck et al.); From Animal Collectives and Complex Networks to Decentralized Motion Control Strategies (A Buscarino et al.); Interplay of Network State and Topology in Epidemic Dynamics (T Gross). Readership: Advanced undergraduates, graduate students and researchers interested in the study of complex networks in a wide range of biological processes and systems."