A New Kind of Science

Having spent much of the last three years thinking about the contents of this book and doing research in the program it establishes, I feel that it is finally time to set the record straight about what this book is and what it means. First, what it does not say. It does not say the universe is a cellular automaton. It does not say we need to throw away existing science. It does not say that every other scientist is the world is an idiot. It does not claim every single minute idea contained within it is new, original, or revolutionary. What it does say, however, is nevertheless as revolutionary as it is inevitable. The fundamental basis for this book, and the science that it tries to build, is the idea that experimental methods are the only way to discover and understand the computational mechanisms that exist in our universe, and indeed to understand the nature of computation itself. Furthermore, it establishes a set of theoretically grounded principles about how these experiments should be conducted, and how their results connect to the rest of science. Despite deeply confused claims to the contrary in some other reviews, this core idea is new. This is fairly easily verified -- just flip to Chapter 3 and ask, how many other scientists search through billions of register machines to discover interesting, complex behavior? Who else enumerates the 4096 s2k2 Turing machines and catalogues the computations they perform? This new kind of science is all about enumerating the *very simplest* computational systems and analyzing their behavior without biases towards any existing scientific tradition. This kind of research is simply not done in computer science, mathematics, physics, or the vague field of complexity theory. Within the first 5 chapters, Wolfram establishes beyond a shadow of a doubt that complex behavior is ubiquitous in even the simplest of computational systems. Clearly, these systems do interesting things, and from a purely intellectual perspective deserve to be a pure field of study, much like pure mathematics. But so what? The rest of the book is dedicated to answering that question. The fact that complexity is so easy to systematically generate suggests a radical approach to science in general. Traditionally, science looks for interesting things in the natural world, and then develops theories to explain certain aspects of their behavior. What Wolfram effectively is suggesting is that by exploring the computational universe, we can start by enumerating and understanding the theories themselves, and then going to the natural world and find places where they apply. At first this sounds crazy and counterintuitive, and from our traditional intuition we "know" that it cannot possibly work. But this book is all about challenging the traditional intuition using actual facts and ultimately fairly simple although abstract arguments. Much of the criticism of the book - even by supposedly reputable scientists - is so laughably superfic

Unlike many reviewers, I read this book completely, including most of the notes. As a computer engineer, I am familiar with many of its ideas, and I have published and peer-reviewed technical papers.With some of the negative reviewers, I will agree that:- The book is long.- It contains self-praise.- Others have explored some of its ideas.If you are in the mindset of peer-reviewing a conference/journal publication, those three things might very much bother you. However, this is not a conference/journal submission! This is a book for a very wide range of audiences, and it is always very difficult to satisfy such a range. IF your own ego can get over the author's self-praise, then you can really enjoy the book for the following:- A thorough exploration of a very important idea, which may sometimes seem obvious but when actually incorporated into our thinking can indeed profoundly affect the way we approach some scientific problems. - A fascinating demonstration of how science selects the problems it considers important simply based on its ability to solve them. This works both ways, with the book pointing out how classic methods completely avoid certain problems, but also happens again in a new way in the course of the book as Wolfram himself selects problems to solve based on the applicability of the concepts he introduces.- A delightful conglomeration of fascinating concepts and problems from all kinds of fields, including computer science, physics, biology, philosophy, etc. If you read the notes, this book takes you on a grand tour of the state of science in many areas, and I can't even imagine the effort that must have gone into compiling, understanding, and organizing all this information. I understand why it took 10 years, and this alone makes the book worth its value.Put your ego and the egos of others aside, and simply enjoy!

Review of Stephen Wolfram, _A New Kind of Science_For three hundred years basic science has idealized mathematical models; this book at the very least makes a comprehensive and clear case for the advantages of the modern alternative: computational models. Probably nowhere else will you find such a clear exposition of the topic. The approach utilizes mainly cellular automata, which are fairly easy to understand and can emulate other computational systems. Hardly any of the central questions of science are untouched in this magnificent work, and the amazing thing is, it can be read and pondered by anyone. (Not in one day, though.)Wolfram begins by developing the basic insights that (a) simple rules can produce systems of great complexity, even of the greatest complexity, which is apparent randomness; and that (b) complexity in systems comes in recurring types which tend to be surprisingly independent of the nature of the systems. From this, after a grand tour of crystal growth, plants and animals, fluid dynamics, financial systems, fundamental physics, cosmology, human perception and analysis, and much else, we arrive at a lengthy discussion of the nature of computation, and finally at Wolfram's grand summation: the Principle of Computational Equivalence. It is this principle that the author believes will eventually revolutionize science.There is no question that the work is ambitious. Critics of the "Age of Science" often hit hardest at its weakness for speculating beyond the data actually available to the sciences. But there is another level of conjecture, namely, speculation about the future development of science itself, perhaps beyond current understanding of the nature of science. This phenomenon, which might be called metaconjecture, we encounter in its pure form on p. 545 of ANKOS, just about in the middle of the book: to derive all the results of quantum theory from computational models "will certainly take an immense amount of work" but Wolfram believes strongly "that in the end it will turn out that every detail of our universe does indeed follow rules that can be represented by a very simple program-and that everything we see will ultimately emerge just from running this program."There are ways in which this book is a major contribution to the philosophy of science even if the author has exaggerated the significance of his ideas. For one thing, one sees very often in science that weaknesses of a well-established approach are discussed openly only when a new approach is being offered. This book sheds light on the nature of traditional science done almost exclusively in terms of mathematical equations, by contrasting this with his approach of looking at computational models using simple rules (Chapters 1-5). (The issue becomes especially clear at p. 474, where the nature of space is being discussed. Continua such as are presupposed by traditional mathematics do not in general yield the complex behavior Wolfram finds interest

This is obviously a very significant work, worthy of careful attention with a critical eye.The more recent research in the book has side-stepped the normal peer reviewed processes of scientific journals. This doesn't make it bad and does indeeed make it more accessible...(bye bye calculus in the mainstream text; also celullar automata doesn't really need it)...but it also means the scientific heavy weights haven't tried to pull it apart yet; so potential holes in the claims of the theory may yet surface.Key book concept => cellular automata => complex processes result from one or two simple augmentation rules being repeatedly applied to an initial cell or row of cells, e.g. color of next cell depends on color of current cell and neighbors. Interesting thing is that whilst the augmentation rules are simple and well defined, some rules lead to a resultant ceullar structure, after several iterations, that appears to be almost random, with structure appearing occassionally, thus the structure has become complex.<p>Wolfram sites many examples in nature and physics where the cellular automata principle can explain behavior. Biological examples, such as plant growth are amongst the most convincing.<p>Cellular automata represents a different way of modeling phenomena in nature. Instead of looking at the end resultant complex structure and creating a correspondingly complex equation to describe it, you would look for the simple underlying rule, that through iteration, leads to the structure under analysis. Is there one underlying rule that ultimately defines all the observable complexity in the universe? How's that for a Holy Grail :-).<p>**The best and most balanced review I have read of Wolfram's book is by Ray Kurzweil. I strongly recommend you read this review. http://www.kurzweilai.net/articles/art0464.html?printable=1**<p>Enjoy the book...