Rating: 
Summary: Readable, wonderful!
Review: This book held my attention (not an easy task). It was readable and enjoyable. You walk away from it understanding complexity better but also understanding the behind-the-scenes in the minds of great scientists and thinkers. This is a must read for anyone dabling in the complexity sciences.
Rating:
Summary: Pretty good rendition of the SFI story
Review: This is a fun book. Tells the story of the Santa Fe institute through the individual stories of the main actors. It's pretty useful if you want to know who's who at SFI and what they have done. The text is clear and engaging. I rated this book as high as I could because it is also scientifically correct as it's not just a story book, actually. While it's not designed to be a technical reference, it's pretty good at telling you: "well this is what this piece of work is, that's what it is based on and that's what it means and that's what it led to". So, actually, the book can easily serve as a primer to the field and it's still a lot of fun to read. Only cloud is that we'd like to know what happened since the early 90's when it was written...
Rating: 
Summary: The Making of the Santa Fe Institute
Review: I bought this book back in 1994, when it was released as a paperback in the UK. I liked it tremendously, and although I let a dozen friends or so borrow it from me to read, I was keeping its track very meticulously in order to get it back every time. Complexity is one of those books that easily gets lost if you are not careful, you know.In short, the book is a chronicle of at the time seemingly unrelated ideas that finally led to forming of the Santa Fe Institute in 1984, and the people who created them: the economist Brian Arthur and his lock-in theory of "increasing returns" (better known to engineers as "positive feedback"); Stuart Kaufmann and his "autocatalytic" models for evolving biological systems; John Holland and his genetic algorithms and genetic programming; Christopher Langton and his "artificial life"; Doyne Farmer with all his experience with chaos theory; and of course the "founding fathers" of the Santa Fe Institute: George Cowan, Kenneth Arrow, and two Nobel-prize winners, Murray Gell-Mann and Philip Anderson. With a PhD in Physics, MA in Journalism and over ten years of service as a senior science writer for one of the world's most prestigious science journals - Science - M. Mitchell Waldrop seems like a role-model science writer. Complexity is his second book, being predecessed by Man Made Minds, a survey of artificial intelligence. This book, however, bears much greater resemblance in style with James Gleick's bestseller Chaos than with his own previous work. Some "historical distance" allows us also a somewhat more critical view on the complexity theory itself. Contrary to the popular expectations of the time, complexity was since forced to follow the same path that chaos, fractals or catastrophe theory - to name a few - traveled before it, and admit that is not The Great Universal Theory of Everything. On the other hand, while the hype is gone, we have to admit that complexity - or "nonlinear science", if you want - is still very actively worked on. So is this book for you? Yes, if you want vivid explanation of one of the most important ideas that shaped the end of the 20th century, and colorful portraits of the people behind it. If nothing else, it will wet your mouth. If Complexity will succeed in winning your interest, you may want to proceed with other popular reading on this topic - almost everyone of the people mentioned before has himself published at least one book. For learning more hard science, however, you should reach for other science monographs and papers.
Rating:
Summary: Flawed yet profoundly illuminating
Review: The complex, self-organising interactive system is a paradigm - like evolution or probability theory - with the power to illuminate vast areas of human experience. "Complexity" brings to life a notion far more important than the much-hyped "chaos", explaining the notions of men like John Holland and Stuart Kauffman. Most notably, the book illuminates the operations of markets and ecosystems. The two fields turn out to have more in common that their respective supporter groups have usually realised, at least since Alfred Marshall's abortive attempt to put a biological spin on economics. Waldrop spends too much time on economist Brian Arthur, but the weaknesses of orthodox, hyper-mathematical economics highlighted in the book's early pages are real enough. And Waldrop knows how to interweave a tale of institutional evolution with the broader tale of an idea's growth.
Rating: 
Summary: Complexity by M. Mitchell Waldrop
Review: Several years ago I read the book at the suggestion of a colleague. He was impressed with the ideas. I was not because the author too uncritical about the difficulties of implementing the Santa Fe agenda of modeling complex systems. At the time, I was particular unimpressed with the tale of Brian Arthur's efforts to forge new grounds in economics. Subsequently, Arthur's efforts got pubished and inspired an unfortunate development in economics. Arthur presented a strained theory of why bad technologies might become adopted. He was inspired to the study by examining what have since proved false charges of "important" bad choices of technology such as typewriter keyboard layout. Unfortunately, the refutations have not caught up with his work and mischief abounds. It adversely affected the Microsoft antitrust case.
Rating: 
Summary: Complexity
Review: This is an overview of complexity theory, an off-shoot and heir apparent of chaos theory. Waldrop models his book very, very closely on Gleick's "Chaos: Making a New Science," which Waldrop (and his publisher) knows was a best-seller. As a result, he summarizes the key positions of complexity theory by way of telling the story of their creators. The heroes of the story are Brian Arthur, an economist who created "lock-in" theory and refuses to go along with the fusty old Adam Smith school of economics that sees everything moving toward "equilibrium." Stuart Kauffman, a truly brilliant and dogged scientist, has a theory of "autocatalysis" that explains away the creationists' position that the emergence of life is too complicated to ever happen by random chance. John Holland provides a mathematical basis and creates computer models for self-emergent and self-organizing systems (including DNA). Christopher Langton is the founder of the "artificial life" branch of science, and Murray Gell-Mann is the Pulitzer-Prize-winning scientist who discovered quarks and now studies the complexities of fragile ecosystems such as the Brazilian rain forest. All of these geniuses happily co-habitate and cross-pollinate their ideas at a rare and remarkable instituion, the Sante Fe Institute. The founding of the institute and its early days in the picturesque setting of an old New Mexico convent provide much of the drama and the local color in Waldrop's tale. All told, however, the book moves much slower than it should and could. The book would have been improved if Waldrop did not have so much "anxiety of influence" over Gleick and his chaos book--Waldrop is inclined to say that complexity theory has outdated or replaced chaos theory, with the implication that Waldrop's book should have the same relationship to Gleick's. In fact, the two theories (and books) can happily coexist and support one another.
Rating:
Summary: The Perfect Introduction to Complexity Theory
Review: For those interested in learning about complexity, Waldrop provides an excellent introduction to the ideas and the personalities of this new science. Rereading this by now classic book lets us appreciate how Waldrop cleared the path for the popularity of Paul Cilliers, Andy Clark, Alicia Juarrero and Stuart Kauffman. A truly self-organizing, complex paradigm in the making!
Rating:
Summary: The best popular work on how complexity arises
Review: The biggest complaint about so-called compositional theories of behavior, mental processes or other complex systems is that they don't actually provide a concise explanation of how you'e actually supposed to build complex behavior from simple agents. What Waldrop has done is to build a simple model for experimenting with just that- how to build complex behavior from simple agents, and this book is a description of the experiments he's done with that system, as well as his experiences with it. "Complexity..." is exceptionally well written, and surprisingly entertaining for a book that is essentially a description of a computer program. I suspect it will become one of the classic texts of the dynamics and evolution of complex systems.
Rating:
Summary: Page Turning Nonfiction!
Review: I highly recommend this book to anyone with an interest in science. One reviewer complained about this being a story, but I really think that being a story makes the science more accessible and allows the reader to experience some of the same excitement as the scientists involved. I found myself turning the pages with anticipation, as if I were reading a novel. Having read this book over a year ago, I still find myself wondering at processes in everyday life.
Rating: 
Summary: Major Disappointment
Review: The title was the most interesting part of this book. But why not change it to more accurately reflect the content to something like "The History of the Santa Fe Institute"? The autobiographical journey the book takes the unsuspecting reader on is filled with too much background and not enough substance. I consider books to be some of the most valuable items in the world today. However, upon completion of this book, I looked at my wife and said "I've got to throw this one away. I don't know of anyone else that I would wish it on and I will never read it again." And so, in the trash can it went. It probably isn't THAT bad of a book, but I could never recommend it to a friend.
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