Adaptive Networks: Theory, Models, and Data

T. Gross and H. Sayama
Springer, Heidelberg, 2009.
ISSN 1860-0832
ISBN 978-3-642-01283-9
doi: 10.1007/978-3-642-01283-9

This book at Springer


Thilo Gross and Hiroki Sayama: Adaptive Networks
Gergely Palla, Péter Pollner, Albert-László Barabási, and Tamás Vicsek: Social Group Dynamics in Networks
Dan Braha and Yaneer Bar-Yam: Time-Dependent Complex Networks: Dynamic Centrality, Dynamic Motifs, and Cycles of Social Interactions
Mark D. Fricker, Lynne Boddy, Toshiyuki Nakagaki, and Daniel P. Bebber: Adaptive Biological Networks
Thimo Rohlf and Stefan Bornholdt: Self-Organized Criticality and Adaptation in Discrete Dynamical Networks
Guido Caldarelli and Diego Garlaschelli: Self-Organization and Complex Networks
Junji Ito and Kunihiko Kaneko: Self-Organization of Network Structure in Coupled-Map Systems
Maoyin Chen and Jürgen Kurths: Dynamical Optimization and Synchronization in Adaptive Complex Networks
Anne-Ly Do and Thilo Gross: Contact Processes and Moment Closure on Adaptive Networks
Leah B. Shaw and Ira B. Schwartz: Noise Induced Dynamics in Adaptive Networks with Applications to Epidemiology
Brian Skyrms and Robin Pemantle: A Dynamic Model of Social Network Formation
Arne Traulsen, Francisco C. Santos, and Jorge M. Pacheco: Evolutionary Games in Self-Organizing Populations
Petter Holme and Gourab Ghoshal: The Diplomat’s Dilemma: Maximal Power for Minimal Effort in Social Networks
Kohji Tomita, Haruhisa Kurokawa, and Satoshi Murata: Graph-Rewriting Automata as a Natural Extension of Cellular Automata
Hiroki Sayama and Craig Laramee: Generative Network Automata: A Generalized Framework for Modeling Adaptive Network Dynamics Using Graph Rewritings


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 influential 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 volume,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 selforganization of topology and dynamics and other remarkably rich dynamical behaviors.

Adaptive networks have for a long time been implicitly contained in models from a wide range of fields including discrete mathematics, computer science, statistical physics, systems biology, social sciences, engineering and medicine. However, only recently research in the different fields has begun to converge on the functioning of the adaptive networks as such. In the different fields, adaptive networks have appeared as a topic of intense research almost at the same time. Consequently, they are currently attacked from many different angles by the tools different disciplineshave established.

It is becoming more and more apparent that adaptive networks could hold the key to many phenomena observed in a wide variety of applications.Major breakthroughs have recently been made and common themes now frequently appear across disciplines. A unified theory of adaptive networks seems within reach.

The book you have at hand, “Adaptive Networks: Theory, Models and Applications”, is the first edited volume that illustrates the dawn of a new research field on the coevolution of topologies and states of complex networks. It showcases the recent advances in the theory, models and applications of adaptive networks by cutting-edge scientists. We hope that the book will play a role in setting the scope and directions of this emerging field of research, by raising the researcher’s awareness to developments in different fields. It can also act as introductory text for the large group of researchers who presently start working on adaptive networks.

The project about this book started in January 2008 when the first editor (T.G.) invited the second editor (H.S.) as a guest scientist to the Max-Planck Institute for the Physics of Complex Systems in Dresden, Germany. For both of us it was clear that the coevolutionary dynamics of states and topologies in adaptive networks will be the next big movement in network research. Fortunately, at that time we had an offer to edit a book in the Springer/NECSI Studies on Complexity Collection; therefore it did not take long to come up with an idea to compile a book that collects the most influential and state-of-the-art in the forefront of adaptive network research. T.G. took the lead of selecting and inviting contributions primarily from statistical physics community, while H.S. invited contributions from empirical network research and computer science communities. All the chapters were included based on invitation only.

The contributors, who collectively represent the cutting edge of the rapidly advancing fields of network research, were enthusiastic about the concept this book aimed to illustrate, and they were extremely cooperative in preparing their chapters on a timely manner following a tight project timeline.We are wholeheartedly thankful for their contribution to and cooperation for this book project, without which it would not have been possible.

We are also very thankful to several people who played key roles in this book project, including: Dan Braha at UMass Dartmouth (Series Editor of the Springer/NECSI Studies on Complexity Collection) and Chris Caron at Springer for inviting us to guest-edit a book; Gabriele Hakuba and Sabine Lehr at Springer for their editorial assistance; Ellen Madison at the Department of Bioengineering at Binghamton University for clerical assistance; and the last but not the least, Cristian Huepe who unconsciously served as a key “hub” in the huge social network that made the two editors get to know each other in the first place and work together for this book. Finally, we thank the Visitor Program of the Max-Planck Institute for the Physics of Complex Systems for financial support.

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