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Rating: 
Summary: Response to other reviews
Review: Alright, seeing "this book should be on the shelf next to Roger Penrose's 'The Emperor's New Mind' and James Gleick's 'Chaos'", and another review saying that the book denies Godel's Theorom, confused me for a while. Then I realized that the latter refered to nueral nets. Assuming that the nets referred to are analog, there is no contradiction. Godel's Theorom proved the incompleteness of formal language systems, a.k.a. digital systems, which constitute a smaller information set than analog systems. Mathematically, analog systems do not meet the neccessary conditions for Godel's Proof to apply. However, the claim to 'completeness', if it be made, is ungrounded. Analog systems simply represent a higher information dimension, not an infinite information dimension.
Rating:
Summary: Response to other reviews
Review: Alright, seeing "this book should be on the shelf next to Roger Penrose's 'The Emperor's New Mind' and James Gleick's 'Chaos'", and another review saying that the book denies Godel's Theorom, confused me for a while. Then I realized that the latter refered to nueral nets. Assuming that the nets referred to are analog, there is no contradiction. Godel's Theorom proved the incompleteness of formal language systems, a.k.a. digital systems, which constitute a smaller information set than analog systems. Mathematically, analog systems do not meet the neccessary conditions for Godel's Proof to apply. However, the claim to 'completeness', if it be made, is ungrounded. Analog systems simply represent a higher information dimension, not an infinite information dimension.
Rating:
Summary: An introduction to complexity for the intelligent reader
Review: Complexity is a new field that touches on almost every one of the sciences, and delivering a solid overview without being superficial is an exceedingingly difficult task; authors Coveny and Highfield have created a book that manages just that. They cover the physical, computational, biological and cognitive sciences, in each case with enough detail to really convey the essence of the field while still remaining very readable to the non-specialist reader. (There's a very detailed- and entertaining- annotated bibliography for those looking for more detail.)While there are currently a number of very good non-technical introductions to complexity theory by such skilled authors as John Casti, Mitchell Feigenbaum and others, this particular volume may well be the best of an excellent lot. Highly recommended to anyone looking for a a non-rigorous, but non-trivial, introduction to the field.
Rating:
Summary: Frontiers of Complexity
Review: Peter Coveney and Roger Highfield, coauthors of The Arrow of Time: A voyage through science to solve time's greatest mystery, performed comprehensive work explaining the evolution of the science of complexity. The authors examined the concept of complexity in such scientific disciplines as mathematics, biology, chemistry and physics.
The authors traced and illustrated the evolution (from reductionism) of complexity in the works of such scientists as:
Charles Babbage - English mathematician, a celebrated icon in the prehistory of computing. Invented Difference Engine No. 1. The Charles Babbage Institute is an historical archive and research center of the University of Minnesota.
George Boole - Better known for the algebras named after him, and as one of the pioneers of modern logic.
Kurt Godel - First to demonstrate that certain mathematical statements can neither be proved or disproved.
Richard Feynmann - Nobel laureate, introduced "universal quantum simulator".
Stuart Kauffman - Author of At Home in the Universe: The search for the Las of Self-Organization and Complexity. The authors also emphasized the beginnings and advances in computing through the pioneering works of: John von Neumann - Invented a self-reproducing automation to show how machine could perform the most basic function of life - reproduction. He is known as the "father of artificial life."
Allan Turing - His work on computers and their relationship with brains made him the "Father of Artificial Intelligence."
John Hopfield - Showed that there is a mathematical mapping of the Sherrington-Kirkpatrick spin-glass model onto a simple type of fully connected neural network model called Hopfield network. What I got from this book: Nothing interests me more than artificial intelligence in my brief exposure to the science of complexity. This book dealt with neural networks so much, I just loved it. On the other hand, its too little - just enough to keep me craving for more! The foreword by Baruch Blumberg, Nobel laureate, left me with a robust and distinct message that I would like to share with you, and I quote: "Each time an experiment is performed to test a hypothesis, more questions are revealed; there is no limit to the mysteries of nature and to our desire to understand them. The study of complexity offers an opportunity to stand back and consider the global interactions of fundamental units - atoms, elementary particles, genes - to create a synthesis that crosses the borders of scientific disciplines, to see a grand vision of nature.
Rating: 
Summary: Good beginning, iffy second half.
Review: This book starts off well enough, with a fascinating chapter on the limits of mathematics, focusing on Godel's refutation of formalism (the idea that the whole of mathematics can be derived from a set of logical statements), followed by a brief history of computers and the computation. But once the authors begin their explanation of complexity, they come off as smug and overzealous about their field. They seem to take every opportunity to belittle other fields of science, and try to convince us that complexity will provide the ultimate explanaion of every facet of the universe, from biology to physics to chemistry to social sciences. This may sound like an exaggeration, but it really isn't: at the beginning of their chapter on complexity in chemical reactions, they dismiss the idea that chemistry (and by extension, biochemistry) can be explanied by quantum physics because the calculations it requires are too complicated. I understand that it is difficult to use quantum physics, and that its effects are only significant on the atomic level, but that does not mean that quantum effects do not exist! The chapter on chemistry marks the end of any reasonable explanation of complexity, and by end of the book complexity is almost completely forgotten, as the writing gushes on about neural networks and aritficial life. It is these later chapters on life and aritificial life that are the most poorly written. The authors commonly say things like "It is becoming clear that obstacles to creating aritfical consciousness may not be as formidable as we had thought", yet provide little proof of this. They basically claim that neural networks are only a few innovations away from becoming fully funcitoning human brains, but they provide a one-sided explanation of their usefulness and fail to mention their failings, especially in cognitive science (which is the study of the brain, of all things). They strongly hint that current ALife programs are creating new life, when they are pretty must just clever programs that manipulate computer memory according to a set of rules. They just don't seem to realize that simulating certain aspects of life with computers and life itself are very different things! We are not even certain that neurons are the basic building block of the brain, yet they are claiming that we now know enough about the brain to create a computerized one in no time. Their argument is very smug and one-sided: the only time they ever mention a criticism to current ALife and AI practices is when they present Roger Penrose's very reasonable hypothesis about how computers cannot simulate intelligence in large part due to their reliance on mathematical logic, which, as Godel proved, can sometimes break down. Yet they quickly dismiss this view, seeming to think that Godel's theorems are nothing more than irrelevant parlor tricks. Their claim that a neural network can be taught to do anything, and therfore can overcome Godel's theorems, is especially poor: we could never teach a human brain to fly, for example, because it (and the body it is in) are not equipped to do this. So why do they think that our arcane artificial neural networks are equipped to create consciousness? Despite this heavy criticism, however, this book is still quite interesting if you are new to complexity, chaos, and artificial life. The author's overexcitement about their field seems to be common when new branches of science emerge, like when AI was first getting off the ground. If you read this book, just realize that its bold claims may be grounded in false hope.
Rating:
Summary: Excellent Primer on Complexity
Review: This book will give you some genuine insight into the emerging (no pun intended) field of Complexity. It presents historical and current research in a way that allows both the researcher and informed layman to get a good grasp on the concepts presented. Both provocative and educational its only flaw is a perhaps too doctrinaire belief that Complexity is the "next step" in science instead of another branch. If you want a good in-depth view of the current state of Chaos and Complexity theories without having to learn all the math this book will give you what you need. It belongs on the shelf next ot Roger Penrose' "The Emperors New Mind" and Gleick's, "Chaos".
Rating:
Summary: Excellent Primer on Complexity
Review: This book will give you some genuine insight into the emerging (no pun intended) field of Complexity. It presents historical and current research in a way that allows both the researcher and informed layman to get a good grasp on the concepts presented. Both provocative and educational its only flaw is a perhaps too doctrinaire belief that Complexity is the "next step" in science instead of another branch. If you want a good in-depth view of the current state of Chaos and Complexity theories without having to learn all the math this book will give you what you need. It belongs on the shelf next ot Roger Penrose' "The Emperors New Mind" and Gleick's, "Chaos".
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