Dynamics of Complex Systems

This is a beautifully written and thought-provoking work that presents the field of complex systems in a unified manner. The writing is highly engaging and stimulating with a broad range of topics. The material is pitched at just the right level, focusing on the concepts without getting buried in unnecessary details, while avoiding superficiality. I highly recommend this excellent book.

This book is designed as a text to introduce graduate students in science to the concepts and methods in the ``science of complexity'' which comprises studies in mathematics, physics, chemistry, biology, computer science, sociology, psychology, economics, anthropology, and philosophy. Written from the perspectives of a physicist, definitions are informal; thus a concise definition of a complex system is not given. The concept of a complex system is introduced through examples, and informally described as having ``a large number of interacting parts'' although ``even a few interacting objects can behave in complex ways.'' More precisely, complexity is defined as ``the amount of information necessary to describe a system.'' Another key concept is the phenomenon of emergence which arises when ``the collective behavior [of a complex system] is not readily understood from the behavior of its parts.'' Dynamics of Complex Systems opens with a long chapter (278 pages) of ``introduction and preliminaries'' which surveys iterative maps; thermodynamics and statistical mechanics; activated processes (glasses); cellular automata; statistical fields; computer simulations; information theory; computation; and fractals, scaling and renormalization. It is suggested that this chapter can serve as the basis for a one-semester course. This introductory chapter is followed by eight chapters devoted two each to four different subjects: neural networks, protein folding, biological evolution, and human civilization. In each of these pairs of chapters, the first is more detailed and the second more general. Thus the first of the two chapters on neural networks describes neural network models (Hopfield's attactor models) whereas the second discusses the phenomenon of sleep and models of mind, with similar divisions of labor in the pairs of chapters on protein folding and on biological evolution. In the final chapter, it is noted that ``human civilization is more complex than we are as individuals.'' Alwyn Scott http://personal.riverusers.com/~rover/

This text provides an excellent introduction to the numerous and diverse techniques used in the study of complex systems. The field of complex systems emerged from a union of ideas from many seemingly disparate areas of research. Where many texts on complex systems speak to this union of ideas, Bar-Yam's text focuses on both the ideas and their implementation in the form of techniques and methods used in the study of these systems. These methodologies originate from many fields of research and several texts could be written about any single one; however I feel that the author has done an excellent job in choosing an important set of problems to present and the detail in which they are presented. This book is appropriate for advanced undergraduates and graduate students. I highly recommended it to my students in my course on complex systems, and if your interests coincide with the topics covered in this book, I highly recommend it to you.

This is a presentation of the models of complexity in a very clear and thought provoking way. Clearly presented for upper undergraduate/graduate level, rich in examples to deepen in the concepts with amounts and amounts of questions, pronblems and challenges, that are completely answered in the text. It unifiess most complexity issues giving a framework picture of todays frontiers.