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Complexity: A Guided Tour Paperback – September 1, 2011

ISBN-13: 978-0199798100 ISBN-10: 0199798109

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Product Details

  • Paperback: 368 pages
  • Publisher: Oxford University Press (September 1, 2011)
  • Language: English
  • ISBN-10: 0199798109
  • ISBN-13: 978-0199798100
  • Product Dimensions: 9.1 x 6 x 1.1 inches
  • Shipping Weight: 1.6 pounds (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (83 customer reviews)
  • Amazon Best Sellers Rank: #36,412 in Books (See Top 100 in Books)

Editorial Reviews

From Booklist

“All theoretical models are wrong, but some are useful.” Both inevitable error and promising usefulness abound in the bold conceptual models that Mitchell surveys in exploring the nascent science of complexity. Readers will marvel at the sheer range of settings in which complex systems operate: from ant hills to the stock market, from T cells to Web searches, from disease epidemics to power outages, complexity challenges theorists’ intellectual adroitness. With refreshing clarity, Mitchell invites nonspecialists to share in these researchers’ adventures in recognizing and measuring complexity and then predicting its cascading effects. Concepts central to thermodynamics, information theory, and computer programming all come into focus in this foray into the recesses of complexity. Still, the analysis illuminates more than explanatory frameworks (such as network diagrams and genetic algorithms); piquant personalities (including Stephen Jay Gould and John von Neumann) also receive illuminating scrutiny. Though Mitchell acknowledges the doubts of skeptics, she still expresses hope that persistent complexity researchers will yet weld their disparate accomplishments into a coherent paradigm. Mind-expanding. --Bryce Christensen --This text refers to the Hardcover edition.

Review

She captures the excitement of research. Ian D. Couzin, Science She writes in an unpretentious style with frequent entertaining and useful anecdotes. Iain D. Couzin. Science --This text refers to the Hardcover edition.

More About the Author

Melanie Mitchell was born in Los Angeles, California. She attended Brown University, where she majored in mathematics and did research in astronomy, and the University of Michigan, where she received a Ph.D. in computer science. At Michigan she worked with her advisor, Douglas Hofstadter, to develop the Copycat project, a computer program that makes analogies. She is currently Professor of Computer Science at Portland State University and External Professor at the Santa Fe Institute. Melanie's most recent book, Complexity: A Guided Tour, won the 2010 Phi Beta Kappa Science Book Award, was named by Amazon.com as one of the ten best science books of 2009, and was longlisted for the Royal Society's 2010 book prize.

Melanie directs the Santa Fe Institute's Complexity Explorer project, which offers free online courses related to complex systems. For more information, go to http://complexityexplorer.org.

Customer Reviews

Unlike many books on complexity, this book is easy to read and highly accessible to general readers.
L. Allen
To be fair, the author mentions that the claims made here are a bit controversial, but I find this part a bit disingenuous to say the least.
Un francais en angleterre
Melanie Mitchell provides an excellent survey of the emerging field of complexity, much like her Introduction to Genetic Algorithms.
Bill C. White

Most Helpful Customer Reviews

189 of 191 people found the following review helpful By Irfan A. Alvi TOP 500 REVIEWERVINE VOICE on May 13, 2009
Format: Hardcover Verified Purchase
This book is easily the best introductory "guided tour" of complexity I know of. It has several key strengths:

1. Mitchell covers many of the major topics which can reasonably be grouped under the umbrella of complexity, so the breadth of the book is excellent. For my benefit and yours, here are the main topics covered, roughly in the order they appear in the book: chaos, information, thermodynamics, Godel's theorem, Turing machines, evolution, genetics, measures of complexity, fractals, self-reproducing automata, genetic algorithms, cellular automata, artificial life, information processing in living systems, analogy-finding algorithms, game theory, networks, power laws, metabolic scaling, random boolean networks, and historical foundations of complex systems research (cybernetics, general systems theory, synergetics, etc.). This long list leaves out some significant complexity topics, but Mitchell's scope is still plentiful for an introductory guided tour.

2. The topics are covered in sufficient depth to clearly convey the key concepts, which reflects the fact that Mitchell is a scientist who really knows the subject. Though the treatment is certainly introductory, rest assured that this isn't a superficial journalistic popularization which drops lots of names and terminology without getting into any real content.

3. Mitchell's writing style is concise and precise, but still friendly and not at all terse. The book is quite easy to read if you have a decent background in general science.

4. General readers will appreciate that there isn't much formal math in the book, yet Mitchell explains things in a way that nicely intimates the outlines of the math for readers who are math-savvy.

5. Mitchell's presentation is sober and honest.
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124 of 129 people found the following review helpful By L. Allen on March 14, 2009
Format: Hardcover
From reviews of the book that appear on the back cover:
"...scholarly yet entertaining..."
"...best general book on this topic."
"...entertains and informs all the way..."

I agree with all of the above. Unlike many books on complexity, this book is easy to read and highly accessible to general readers. More importantly to me as a graduate student, this book is more fascinating and in many ways more thought-provoking than math-heavy textbooks for specialists/academics.

I bought the book because of my interest in artificial intelligence, and I highly recommend this book to anyone interested in artificial intelligence, computer science, or biology. What I like most about the book is that it provides me with a fresh perspective/synthesis that pulls together what has been going on in different fields and subfields. For example, in computer science, we are taught all the time about how important it is for programs to be able to scale, but we are not given a biological perspective of how genes scale so well. This book does that in it's chapter on scaling.

Each chapter includes historical perspectives and/or real-world examples. For example, the chapter on genetic algorithms includes a quick survey of the companies and organizations that have recently benefited from using them.

The book also includes a chapter on why computers are still pretty dumb (lack general intelligence). The chapter reiterates that analogy understanding may be the holy grail to developing artificial general intelligence. (Like most people, I agree with the author that artificial general intelligence, AGI, is not going to happen anytime soon.) Some relevant info about the author from Wikipedia: "She received her PhD in 1990 from the University of Michigan under Douglas Hofstadter and John Holland, for which she developed the Copycat cognitive architecture. She is the author of "Analogy-Making as Perception.""
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57 of 58 people found the following review helpful By Karen D. on May 7, 2009
Format: Hardcover Verified Purchase
This book really lives up to its title, "Complexity: A Guided Tour." Dr. Mitchell has turned her Santa Fe Institute lectures on the foundations of Complexity into a very interesting, readable book suitable for academics, professionals, students, and interested laypeople. She explains how complexity fits into the history of scientific knowledge. She relates it to the rapidly expanding field of information science, as influenced by biological rather than mechanical models. She even explains how computer models relate to living systems as information processors.

Having read many scholarly papers on these topics, I can vouch for the clarity and accuracy of her work. She certainly doesn't need any endorsement, though; as a successful doctoral student under the renowned Doug Hofstadter and now a professor at Santa Fe, she is in the inner circle of complexity scientists today. If only her book had come out a year or two ago! It puts in one place many ideas we used to have to search out and integrate on our own!

One note: the mathematics of complexity science can be daunting. Dr. Mitchell has done a terrific job expressing & explaining those concepts. Unlike many of the complexity books in print, hers is both intelligent and accessible. Highly recommend it!
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30 of 30 people found the following review helpful By Dave Snell on February 12, 2010
Format: Hardcover Verified Purchase
Complexity: A Guided Tour, by Melanie Mitchell, Ph.D.

One of my favorite books from the early 1980s was a huge tome titled Gödel, Escher, Bach: An Eternal Golden Braid, by Douglas Hofstadter, a pioneer in Artificial Intelligence (AI). Hofstadter described GEB (the initials became a popular abbreviation for his book) as "a metaphorical fugue on minds and machines in the spirit of Lewis Carroll". At the time I was just getting interested in AI and I found GEB fascinating. Apparently, I was not alone. Melanie Mitchell, then a high school mathematics teacher in New York, found it "one of those life-changing events that one can never anticipate".

She wrote to Hofstadter that she wanted to study under him as a graduate student. Receiving no reply, she later approached him in person when he gave a lecture at MIT. He handed her off to a graduate student. She was "disappointed, but not deterred" and after several more follow-up calls to him, she managed, through her persistence, to convince him of her passion for AI - a topic that eventually was absorbed into Complexity Science. Eventually, she moved to Michigan and earned her Ph.D. under Hofstadter and John Holland, another complexity science pioneer. I mention this history to try to convey the contagious enthusiasm for complexity science that Dr. Mitchell exudes in her book. She seems to prefer the term complexity sciences, since this is such a cross disciplinary subject; but in this review I'll use the more common term complexity science.

Mitchell starts with an acknowledgement to the Santa Fe Institute (SFI) where she directed an SFI Complex Systems Summer School.
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