The theory of nonlinear, complex systems has become by now a proven problem-solving approach in the natural sciences. And it is now also recognized that many if not most of our social, ecological, economical and political problems are essentially of a global, complex and nonlinear nature. And it is now further accepted than any holistic perspective of the human mind and brain can hardly be achieved by any other approach. In this wide-ranging, scholarly but very concise treatment, physicist, computer scientist and philosopher klaus mainzer discusses, in essentially nontechnical language, the common framework behind these ideas and challenges. Emphasis is given to the evolution of new structures in natural and cultural systems and we are lead to see clearly how the new integrative approach can give insights not available from traditional reductionistic methods. The fifth edition enlarges and revises almost all sections and supplements an entirely new chapter on the complexity of economic systems. From the reviews of the fourth "this book is ambitious, incredibly erudite with 22 pages of references, and is indisputably clearly and beautifully written and illustrated. It is perfectly suited to a first course on the science of complexity. Even beginners and young graduate students will have something to learn from this book." (andre hautot, physicalia, vol. 57 (3), 2005) "all-in-all, this highly recommended book is a wonderful resource for intuitive basic ideas in the need of rigorous formulation." (albert a. Mullin, zentralblatt math, vol. 1046, 2004) "readers of this book will enjoy mainzer's exposition, which is based on a tight coupling between classical and historical concepts from plato and aristotle to modern, mathematical and physical developments . Every chapter begins with a section designed to orient the reader to the perspective of philosophical developments through the ages pertinent to the topic at hand.
It's getting a bit old, thus the state of the art in some of the chapters moved on. Nonetheless the underlying principles seem solid enough, and thus loads of food for thought, how to apply more of the nonlinear thinking more, and more appropriately.
It brings in examples from loads of other work, though those bits could have used some more explanations (often it looked mostly just a lifted chart without much details and some general handwaving).
In general it's worthwhile, even when it doesn't quite stand on its own (need some basics, and best is to follow up on the interesting parts for more details).
Вообще очень интересная книга, полезно было освежить то, что я давно читал у Пригожина и Чернавского. Автор пытается касаться современных тем, таких как IT, AI. Но в некоторых местах закапывается в такие подробности, которые лишние в обзорной, в целом, книге.