- Hardcover: 1192 pages
- Publisher: Wolfram Media; 1 edition (May 14, 2002)
- Language: English
- ISBN-10: 1579550088
- ISBN-13: 978-1579550080
- Product Dimensions: 8.1 x 2.5 x 9.7 inches
- Shipping Weight: 5.6 pounds (View shipping rates and policies)
- Average Customer Review: 393 customer reviews
- Amazon Best Sellers Rank: #75,046 in Books (See Top 100 in Books)
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A New Kind of Science 1st Edition
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Physics and computer science genius Stephen Wolfram, whose Mathematica computer language launched a multimillion-dollar company, now sets his sights on a more daunting goal: understanding the universe. Wolfram lets the world see his work in A New Kind of Science, a gorgeous, 1,280-page tome more than a decade in the making. With patience, insight, and self-confidence to spare, Wolfram outlines a fundamental new way of modeling complex systems.
On the frontier of complexity science since he was a boy, Wolfram is a champion of cellular automata--256 "programs" governed by simple nonmathematical rules. He points out that even the most complex equations fail to accurately model biological systems, but the simplest cellular automata can produce results straight out of nature--tree branches, stream eddies, and leopard spots, for instance. The graphics in A New Kind of Science show striking resemblance to the patterns we see in nature every day.
Wolfram wrote the book in a distinct style meant to make it easy to read, even for nontechies; a basic familiarity with logic is helpful but not essential. Readers will find themselves swept away by the elegant simplicity of Wolfram's ideas and the accidental artistry of the cellular automaton models. Whether or not Wolfram's revolution ultimately gives us the keys to the universe, his new science is absolutely awe-inspiring. --Therese Littleton
From Library Journal
Galileo proclaimed that nature is written in the language of mathematics, but Wolfram would argue that it is written in the language of programs and, remarkably, simple ones at that. A scientific prodigy who earned a doctorate from Caltech at age 20, Wolfram became a Nobel-caliber researcher in the emerging field of complexity shortly thereafter only to abscond from academe and establish his own software company (which published this book). In secrecy, for over ten years, he experimented with computer graphics called cellular automata, which produce shaded images on grid patterns according to programmatic rules (973 images are reproduced here). Wolfram went on to discover that the same vastly complex images could be produced by even very simple sets of rules and argues here that dynamic and complex systems throughout nature are triggered by simple programs. Mathematical science can describe and in some cases predict phenomena but cannot truly explain why what happens happens. Underscoring his point that simplicity begets complexity, Wolfram wrote this book in mostly nontechnical language. Any informed, motivated reader can, with some effort, follow from chapter to chapter, but the work as a whole and its implications are probably understood fully by the author alone. Had this been written by a lesser scientist, many academics might have dismissed it as the work of a crank. Given its source, though, it will merit discussion for years to come. Essential for all academic libraries. [This tome is a surprise best seller on Amazon. Ed.] Gregg Sapp, Science Lib., SUNY at Alban.
- Gregg Sapp, Science Lib., SUNY at Albany
Copyright 2002 Cahners Business Information, Inc.
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The author demonstrates that cellular automata are capable of computing anything that can be computed by today's computing machines. He also shows that exceedingly simple rules can lead to exceedingly complex results. An implication of this is claimed to be that cellular automata can model most anything in the known universe and can serve as a model for exploring significant questions about our universe.
The author explores significant fields of science using the notions of cellular automata. For example, the chapter on biological evolution has many very interesting insights. The author also uses cellular automata to make what I would call a "first order" model of spacetime that includes the properties of time and causality. I found this to be quite interesting.
Reading this book also affords a glimpse for us non-braniacs into the course, from conception to fruition, of an actual scientific inquiry. This is a rare opportunity.
The author's intent, as I see it, is to offer ideas; to provide what I would call "plausibility arguments" for his claim that he has discovered a fundamental property of nature (the "Principle of Computational Equivalence"). I think he succeeds in making his claim plausible.
The author is not claiming that this book contains any actual, formal, scientific, final and conclusive proof of indisputable law by any completely rigourous method.
But our intuition can be notoriously misleading - that's why science is what it is.
While I am kind of impressed by this book, reviews by significant people in the scientific community seem to be mixed.
Therefore, paraphrasing what the author himself has said, the final review will be written only after a long time.
The central idea (as far as I can tell) is that the way we do science right now is by trying to reverse-engineer complex things to explain them, or to look for solutions to problems. Whereas if we went the other direction, looking for the kind of complexity that arises from simple starting points with simple rules, we could discover things we haven't imagined.
This is especially interesting when you consider the potential for running almost limitless programs that we will we have at our fingertips once quantum computing is a reality.
While there is an "ooh, aah" factor about some of the graphs, unlike some other reviewers I think they could stimulate people in other disciplines to think about their problems in new ways eg nanotechnology, biology etc. That is not a bad thing. The curious thing is that some of the graphs are so evocative of actual structures that one sees in electron microscope scans that one feels that there may be some deep linkage which could have predictive value. It's the elucidation of that potential that would be truly fundamental ie something that shows in a predictive sense how elements with different atomic weights etc will be structured and how combinations would be structured.
Obviously Steve Wolfram has got up a few noses for some reason judging by some of the rather stentorian criticisms I have read. I will plough on with the book on the basis that it may provide some insights that can be developed further. While it may not be Principia Mathematica in terms of its completeness, novelty and relevance, if a handful of the right people get some insights from it and develop them it will have proved a useful contribution notwithstanding the reservations.