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The Making of the Santa Fe Institute,
This review is from: Complexity: The Emerging Science at the Edge of Order and Chaos (Penguin Science) (Paperback)
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.