Complexity And Evolution Of Dissipative Systems

This book focuses on the dynamic complexity of neural, genetic networks, and reaction diffusion systems. The author shows that all robust attractors can be realized in dynamics of such systems. In particular, a positive solution of the Ruelle-Takens hypothesis for on chaos existence for large class of reaction-diffusion systems is given. The book considers viability problems for such systems - viability under extreme random perturbations - and discusses an interesting hypothesis of M. Gromov and A. Carbone on biological evolution. There appears a connection with the Kolmogorov complexity theory. As applications, transcription-factors-microRNA networks are considered, patterning in biology, a new approach to estimate the computational power of neural and genetic networks, social and economical networks, and a connection with the hard combinatorial problems.

Spontaneous pattern formation in nonlinear dissipative systems far from equilibrium occurs in a variety of settings in nature and technology, and has applications ranging from nonlinear optics through solid and fluid mechanics, physical chemistry and chemical engineering to biology. This book explores the forefront of current research, describing in-depth the analytical methods that elucidate the complex evolution of nonlinear dissipative systems.

This new edition also treats smart materials and artificial life. A new chapter on information and computational dynamics takes up many recent discussions in the community.

In the decades the of the formation of structures past subject spontaneous in far from has into a branch of - systems equilibrium major physics grown search with ties to It has become evident that strong neighboring disciplines. a diverse of can be understood within a common mat- phenomena range matical framework which has been called nonlinear of continuous dynamics This name the close to the field of nonlinear systems. emphasizes relationship of with few of freedom which has evolved into a dynamics systems degrees mature in the recent features mathematically subject past. Many dynamical of continuous be described reduction few can a to a systems actually through of freedom and of the latter of continue to degrees properties type systems of continuous the inspire study systems. The of this book is to demonstrate the numerous goal through examples that exist for the of nonlinear the opportunities study phenomena through tools of mathematical and use of common analyses dynamical interpretations. Instead of overview of the a providing comprehensive rapidly evolving field, the contributors to this book are to communicate to a wide scientific trying audience the of what have learnt about the formation of essence they spon- neous structures in continuous and about the dissipative systems competition between order and chaos that characterizes these It is that systems. hoped the book will be even to those scientists whose not helpful are disciplines the authors.

An exploration of how approaches that draw on evolutionary theory and complexity science can advance our understanding of economics. Two widely heralded yet contested approaches to economics have emerged in recent years: one emphasizes evolutionary theory in terms of individuals and institutions; the other views economies as complex adaptive systems. In this book, leading scholars examine these two bodies of theory, exploring their possible impact on economics. Relevant concepts from evolutionary theory drawn on by the contributors include the distinction between proximate and ultimate causation, multilevel selection, cultural change as an evolutionary process, and human psychology as a product of gene-culture coevolution. Applicable ideas from complexity theory include self-organization, fractals, chaos theory, sensitive dependence, basins of attraction, and path dependence. The contributors discuss a synthesis of complexity and evolutionary approaches and the challenges that emerge. Focusing on evolutionary behavioral economics, and the evolution of institutions, they offer practical applications and point to avenues for future research. Contributors Robert Axtell, Jenna Bednar, Eric D. Beinhocker, Adrian V. Bell, Terence C. Burnham, Julia Chelen, David Colander, Iain D. Couzin, Thomas E. Currie, Joshua M. Epstein, Daniel Fricke, Herbert Gintis, Paul W. Glimcher, John Gowdy, Thorsten Hens, Michael E. Hochberg, Alan Kirman, Robert Kurzban, Leonhard Lades, Stephen E. G. Lea, John E. Mayfield, Mariana Mazzucato, Kevin McCabe, John F. Padgett, Scott E. Page, Karthik Panchanathan, Peter J. Richerson, Peter Schuster, Georg Schwesinger, Rajiv Sethi, Enrico Spolaore, Sven Steinmo, Miriam Teschl, Peter Turchin, Jeroen C. J. M. van den Bergh, Sander E. van der Leeuw, Romain Wacziarg, John J. Wallis, David S. Wilson, Ulrich Witt

This wide-ranging handbook studies and defines the paradigm of evolutionary economic geography. The distinguished contributors highlight the key conceptual, theoretical and empirical advances, and present a clear statement of their aims, objectives and methods.

Nonlinear dynamics is now recognized as playing a crucial role in a wide variety of disciplines. But what is only just beginning is the important process of cross fertilization and transfer of knowledge and expertise from one area to another. This book is intended to promote this process which will undoubtedly contribute greatly to furthering our understanding of complex systems. Contributions are provided by leading experts from the areas of sociology, cognitive science, chemistry, physiology, ecology, economics, neural networks and physics.