What enables individually simple insects like ants to act with such precision and purpose as a group? How do trillions of neurons produce something as extraordinarily complex as consciousness? In this remarkably clear and companionable book, leading complex systems scientist Melanie Mitchell provides an intimate tour of the sciences of complexity, a broad set of efforts that seek to explain how large-scale complex, organized, and adaptive behavior can emerge from simple interactions among myriad individuals. Based on her work at the Santa Fe Institute and drawing on its interdisciplinary strategies, Mitchell brings clarity to the workings of complexity across a broad range of biological, technological, and social phenomena, seeking out the general principles or laws that apply to all of them. Richly illustrated, Complexity: A Guided Tour--winner of the 2010 Phi Beta Kappa Book Award in Science--offers a wide-ranging overview of the ideas underlying complex systems science, the current research at the forefront of this field, and the prospects for its contribution to solving some of the most important scientific questions of our time.
Complexity: A Guided Tour
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“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.
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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
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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, working with her advisor Douglas Hofstadter on 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, and does research in the fields of artificial intelligence, cognitive science, and complex systems. She lives in Portland, Oregon with her husband and two sons.
Customer Reviews
Most Helpful Customer Reviews
158 of 159 people found the following review helpful
Format:Hardcover|Amazon 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. She naturally highlights the potentials and promise of complex systems science, but she also openly acknowledges its past dead ends and likely future limitations.
6. There are biographical notes interspersed throughout the book, which adds a nice human touch.
For completeness, I'll note that I did notice a few technical errors in Mitchell's initial discussion of immunology. But these errors don't invalidate the general message, and can be overlooked, considering the overall excellence of the book.
The bottom line is that I highly recommend this book to anyone interested in complexity (how could you not be?). It's a perfect introduction for beginners, and people well-versed in the subject will also appreciate the convenience of having a high-quality broad overview within the covers of just one book.
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. She naturally highlights the potentials and promise of complex systems science, but she also openly acknowledges its past dead ends and likely future limitations.
6. There are biographical notes interspersed throughout the book, which adds a nice human touch.
For completeness, I'll note that I did notice a few technical errors in Mitchell's initial discussion of immunology. But these errors don't invalidate the general message, and can be overlooked, considering the overall excellence of the book.
The bottom line is that I highly recommend this book to anyone interested in complexity (how could you not be?). It's a perfect introduction for beginners, and people well-versed in the subject will also appreciate the convenience of having a high-quality broad overview within the covers of just one book.
116 of 121 people found the following review helpful
By L. Allen
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.""
"...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.""
52 of 53 people found the following review helpful
By Karen D.
Format:Hardcover|Amazon 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!
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!
Most Recent Customer Reviews
1.0 out of 5 stars
Very weak overview of Complexity
I'm amazed at the number of positive reviews here, because this author has a weak grasp of her subject and presents it very poorly, and inaccurately in places. Read more
Published 10 days ago by A. Mead
1.0 out of 5 stars
A waste of time
I don't know about others, but I read a great number of books and my time is limited. This is a book which could have been written in about 50 pages instead of 300+ and am not sure... Read more
Published 1 month ago by Beau Sabreur
5.0 out of 5 stars
Great introduction to complexity science
Mitchell writes a great introduction to the emerging science of complexity. Keeps the reader engaged with a number of interesting applications as well as highlighting some of the... Read more
Published 1 month ago by F. Grab
3.0 out of 5 stars
A good history of the subject
I liked this book in many ways and it told a really important story. But I found some parts of the book frustrating. Read more
Published 2 months ago by David Richards
4.0 out of 5 stars
Excellent overview
The reading is easy although the content quite profound. An excellent overview of what has been going on in the study of complexity.
Published 2 months ago by De Croock Roger
5.0 out of 5 stars
Earth-shaker
Brilliant! I have a new carreir opening as a possibility to me as complexity scientist. Inspirating, instigating, and very well written, in a boringness-proof style. Loved IT.
Published 3 months ago by Zeff
5.0 out of 5 stars
On the Doorstep of a Fascinating New World
Whether you're a newbie to the topic of complexity, an aficionado that has been keeping your eye on the topic for a while now, or a dedicated member of the complexity community... Read more
Published 4 months ago by Daniel Murphy
5.0 out of 5 stars
Great Book
This book is a great start to learning about complex adaptive systems. Mitchell, being from Santa Fe Institute, knows a lot about the topic. Read more
Published 6 months ago by Chris
4.0 out of 5 stars
It's a Guided Tour, Not a Detailed Treatment
In Complexity: A Guided Tour, Melanie Mitchell describes bits and pieces of the emerging field presently being called "complex systems science. Read more
Published 9 months ago by M. Edwards
2.0 out of 5 stars
This just wasn't very good
I actually came across the idea of complexity in the context of a book on Economics that I was reading (Currency Wars: The Making of the Next Global Crisis (Portfolio)), and I... Read more
Published 9 months ago by Lemas Mitchell
