Frontiers of Complexity

In this groundbreaking book, Peter Coveney and Roger Highfield, co-authors of the highly praised The Arrow of Time, explore how complexity is transforming not only the way we think about the universe, but also the very assumptions that underlie conventional science. Coveny and Highfield define complexity as a new way of thinking about the behavior of interacting units, be they atoms, ants in a colony, neurons firing in a human brain, or people in a society. Complexity reaches far beyond the concept of chaos and represents a profound shift away from the reductive principle that has guided science for centuries. As Coveney and Highfield brilliantly illustrate, the rise of the electronic computer provided both the key and the catalyst to our exploration of complexity. With the promise of a new generation of computers that runs on light, manipulates fuzzy logic and exploits the bizarre properties of quantum mechanics, the authors reveal how we are set to witness a huge expansion in the efforts to unravel the mysteries of complexity. Frontiers of Complexity takes us inside the laboratory where scientists are evolving the genetic molecules that enables life to emerge on Earth, and reveals universes in cyberspace where organisms compete for resources as they reproduce, mutate and evolve. We witness the utterly realistic behaviour of a school of virtual fish, and encounter scientist who have accurately modelled the one million neurons that make up the brain of a bee. Compelling in its clarity, vast in its scope and vibrant with the excitement of new discovery, Frontiers of Complexity is an arresting account of how far science has come in the past fifty years, and an essential guide to the science of the future. --- from book's Prologue

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.

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.

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".

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.