This book explains why complex systems research is important in understanding the structure, function and dynamics of complex natural and social phenomena. Readers will learn the basic concepts and methods of complex system research.

This book explains why complex systems research is important in understanding the structure, function and dynamics of complex natural and social phenomena. It illuminates how complex collective behavior emerges from the parts of a system, due to the interaction between the system and its environment. Readers will learn the basic concepts and methods of complex system research. The authors show that very different complex phenomena of nature and society can be analyzed and understood by nonlinear dynamics since many systems of very different fields, such as physics, chemistry, biology, economics, psychology and sociology have similar architecture. The book is not highly technical mathematically, but teaches and uses the basic mathematical notions of dynamical system theory, making the book useful for students of science majors and graduate courses. Still, it is intended to be readable for a more general audience, for those who ask: What really are complex systems?

Complex Systems: The Intellectual Landscape.- History of Complex Systems Research.- From the Clockwork World View to Irreversibility (and Back?).- The Dynamic World View in Action.- The Search for Laws: Deductive Versus Inductive.- Statistical Laws: From Symmetric to Asymmetric.- Simple and Complex Structures: Between Order and Randomness.- Complexity of the Brain: Structure, Function and Dynamics.- From Models to Decision Making.- How Many Cultures We Have?.

This book is, of course about complexity. The title of the book, as you may recognize was motivated (excuse me for using this very mild expression) by Daniel Dennett's Consciousness Explained [130]. Dennett's intention was to explain consciousness as the emergent product of the interaction among c- stituents having physical and neural character. The goal of this book is to explain how various types of complexity emerge due to the interaction among constituents. There are many questions to be answered, how to understand, control, decompose, manage, predict the many-faced complexity. After tea- ing thissubjectforseveralyearsIfeelthatthe time hascome toputthe whole story together. The term "complex system" is a buzzword, but we certainly don't have a single de?nition for it. There are several predominant features of compl- ity. Complex processes may show unpredictable behavior (which we still try to predict somehow), may lead to uncontrolled explosion (such in case of epilepsy, earthquake eruptions or stock market crashes). One of the char- teristic feature of simple systems is, that there is a single cause which implies a single e?ect. For large class of complex systems it is true that e?ects are fed back to modify causes. Biological cells belong to this class. Furthermore they are open to material, energetic and information ?ow by interaction with their environment, still they are organizationallyclosed units. Another aspect of complexity is the question how collective phenomena emerge by some se- organized mechanisms.