Principles of Systems Science (Understanding Complex Systems)

This is a general and non-technical treatment. Each of many areas is covered in (non-mathematical) detail and each is fitted into a fantastically interesting coherent whole. Many of the definitions and insights are absolutely first rate. Spectacular. I am not an engineer, and I am somewhat new to systems thinking; this is perfect for me. If math is your oyster, you have studied complexity, cybernetics, information, computation, evolution and other relevant topics, this might not extend your knowledge much as it is written for non-specialists. Check the (vast) table of contents. If you are non-technical like me, and you are willing to invest the time, and you care about how things work; the rewards are quite rich. More than worth it if... The labor is not so much due to the difficulty of the topic(s); it is just that there is a lot to cover. Liken it to an entire general biology textbook, and it doesn't seem so enormous. If you don't have any background in complexity, information etc. You will probably need a tutor, or a mature drive to learn. Please note that although there is an abundance of extremely valuable knowledge in here the writing is occasionally a little fluffy, and redundant, so things go a little slower than might be optimal. Maybe skip the chapters on evolution. One of the 4 most important books I have read. I am taking extensive notes, and my total investment will be maybe 100 hours of intense focus. I do have some background in much of this. This topic will change you. A very, very important area of knowledge.

One of the most eye-opening books I have ever read. My particular interest is in why people behave the way they do. In lifelong pursuit of this understanding, I studied behavioral genetics, then neuroscience. I read up on psychology, then evolutionary psychology, then psychotherapy, then sociology. Each field gave me a little piece of the puzzle, but not the big picture. I began to see that the understanding I was after was never going to come from the typical reductionist academic scholarship of ever increasing specialization. What was needed was some completely new type of scholarship, a framework for integrating across academic knowledge silos, a way to zoom out and get a crude look at the whole. In my struggle to find such a field, I stumbled onto the field of Big History, which integrates history from the Big Bang to the present drawing on many academic specialties in the process. In that field, you can see that the history of the universe is this: a stable system emerges from chaos, then groupings of those systems form larger more complex systems, then those form into megasystems, on up. But what I didn’t really understand from Big History is how or why the systems form. And that question brought me to this book. From the first sentence of the preface, I knew these were my people. The first sentence is “This book is about understanding.” And it proceeded to blow my mind over and over again with its explanatory power.Big History explains what happened, System Science explains how it happened and Universal Darwinism explains why it happened. I think a course in each of these three topics, or even a single course integrating the three, could form the foundation of a whole new intellectual approach to understanding the world, one that is a much needed compliment to reductionist endeavors. And regarding my particular interests, I now think that our best hope of understanding human behavior is to address it from this tripartite foundation.

My initial interest in the book and this field came from reading Ludwig von Bertalanffy's General System Theory. Although in retrospect, reading Principles of Systems Science first would have been better.The authors of Principles of Systems Science practice what they teach, often switch between fields, effectively showing how economics, biology, business, and myriad other subjects can all be seen through the lenses of Systems Science. This is part and parcel of Systems Science. Bertalanffy does the same thing in General System Theory. I personally like that, it's the way I think, so it's quite natural to me even though I'm not well versed in some of these subjects (notably biology), but to some it might be off-putting.While the book does not require any specific advanced math, any math is well identified in the Quant boxes, there is frequent use of Graph Theory.Also a number of chapters rely heavily on Evolution, while again no preexisting knowledge is required to understand the book, already knowing of the concept of natural selection goes a long way in keeping up.In its aspect as an introduction to the field the book is successful. As the title indicates, it's a textbook for the principles of Systems Science. Each Chapter has a reasonably sized, but always effectively curated bibliography pointing the way to learn more about a specific topic.The most effective part of the book is as a way to learn to think in a different way, thinking in terms of systems, instead of one to one cause and effect. Now I find that I see systems everywhere, I'm taking that as an indication that reading the book is working.

A clearly written overview of many aspects of system science. Enlightening in many ways. Ever want to know what 'emergence' really means? How about its inverse, the loss of complexity and the many ways it may be measured? This is the book for you. Complex systems are covered in terms of physical / structural components, nature of control systems and information use, matter and energy transformation, dynamics, and evolution. The only criticism I have in in the last chapter, an overview of system engineering. The authors refer the reader to other books, but nevertheless overlook a major aspect of system engineering: the coverage of failure cases and off-nominal inputs. These aspects should always be emphasized (rather than skipped) because they are fundamental to virtually all critical accidents (think airplane control systems, 3-mile Island, chemical factory accidents, etc.). Look elsewhere for better coverage of the system engineering discipline.

A comprehensive review of Systems Science. Very good reference book.

Mobus and Kalton have delivered tons of insight into systems science, going well beyond the somewhat humble "Principles"-only in the book's title. Especially chapter 9 (the longest), on the role of information and computation in CASs (Complex Adaptive Systems), is insightful. Mobus coming from an engineering and "hard sciences" background, Kalton bringing in the more philosophical perspective, the two authors complete each other beautifully. I am using parts of this book's contents as background material in a course on Systems Architecting I deliver - as a professional - to such audiences as automotive R & D engineers, NATO systems architects and various UML modelers. It must be said that the books I admit into the sacrosanct inner circle of my courses' background material are very, very scarce!Quantitative treatment is somewhat scarce, and concentrated in so-called "Quant Boxes" (there are also "Think Boxes" and "Question Boxes"); this is in line with the authors' intention to keep the book as accessible to various publics as possible.A last remark must be made here on the authors extensively citing Wikipedia links - when they think the Wikipedia entry on a topic is sound and solid. They even make a gentle call for a donation upon the reader; this makes the book even more sympathetic to me.All in all a great achievement, that lends itself excellently to such uses as a textbook or as a course's provider of background material.

Vorsicht! Die Ausgabe ist in schwarz-weiss, die Orginalausgabe enthält viele Kolorbilder. Der Inhalt finde ich interessant: ein gutes Lehrbuch der Systemtheorie.

Peu de livres concernant la systémique traitent de cette matière si détaillée et instructive....et plaisir de le lire.....et en plus ça me sert pour mon travail de Consultant....