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What do traffic jams, stock market crashes, and wars have in common? They are all explained using complexity, an unsolved puzzle that many researchers believe is the key to predicting – and ultimately solving—everything from terrorist attacks and pandemic viruses right down to rush hour traffic congestion.
Complexity is considered by many to be the single most important scientific development since general relativity and it promises to make sense of no less than the very heart of the Universe. Using it, scientists can find order emerging from seemingly random interactions of all kinds, from something as simple as flipping coins through to more challenging problems such as the patterns in modern jazz, the growth of cancer tumours, and predicting shopping habits.
- Sales Rank: #170449 in Books
- Brand: Johnson, Neil F.
- Published on: 2009-10-01
- Released on: 2010-10-01
- Original language: English
- Number of items: 1
- Dimensions: 7.93" h x .72" w x 5.09" l, .61 pounds
- Binding: Paperback
- 256 pages
Review
"Johnson's book fills a long-overdue need for an engaging semipopular book about complexity science, one that is also strong on the underlying scientific and theoretical concepts." "Highly recommended." Choice "Neil Johnson has provided a readable account of the science of complexity" Oxford Times
About the Author
Neil Johnson is the head of a new inter-disciplinary research group in Complexity at University of Miami in Florida. Previously he was Professor of Physics and co-director of research collaboration into Complexity at Oxford University.
Most helpful customer reviews
69 of 70 people found the following review helpful.
A fine introduction to what Complexity is all about.
By Amazon Customer
If you are unfamiliar with Complexity Theory ("The Science of Sciences") then this is a great book to start with. Neil Johnson has done an impeccable job of keeping the intricacies of Complexity within a very manageable framework that any layman can understand. Take this quote for example: "Complexity can be summed up by the phrase "Two's company, three is a crowd." In other words, Complexity Science can be seen as the study of the phenomena which emerge from a collection of interacting objects - and a crowd is a perfect example of such an emergent phenomenon, since it is a phenomenon which emerges from a collection of interacting people." The real strength of this book lies in Johnson's unsophisticated and plain approach towards Complexity Science which he couples with many real world examples. But neither does Johnson leave anything out; Self-Similarity, Fractals, Power-Laws, Networks, etc. - it's all here.
My only complaint about this book comes on page 100. Here, Johnson explains how the "six degrees of separation" network was conceived by Stanly Milgram in 1967. I am sure that Johnson knows that this was debunked by later research, but Johnson fails to mention this in the book (one only has to look to Wikipedia, Complexity: A Guided Tour by Melanie Mitchell or The Numbers Game: The Commonsense Guide to Understanding Numbers in the News, in Politics, and inLife for confirmation. I do not fault Johnson here because given the 'basic' level at which this book was written, he probably didn't feel like complicating the issue - the point he was trying to make was satisfied - and he therefore surely didn't feeling like going into the whole mess by upending the urban legend. So, with that aside, I do recommend this book as a great introduction to Complexity and recommend Complexity: A Guided Tour by Melanie Mitchell for the interested reader as a great book to continue learning about Complexity Science.
1 of 1 people found the following review helpful.
It's ok, I guess
By Boris Glebov
I came to this book as a physicist with a hobby-level interest in complexity theory. And to me this was a disappointment. Mathematical depth is non-existent. In its course, the book goes over several problems, approaching them from the point of view of complexity theory. This perspective is interesting and instructive, sure enough. However, these explanations tend to be too long and convoluted. A point that could be made effectively in a paragraph often takes several pages. Even for a non-scientist looking for an overview of a subject, I can't imagine this is a helpful treatment.
Basically, imagine someone's dad went to a lawn mower convention, and now insists on telling everyone all the cool lawn mower gadgets he saw. It's exactly like that, except it's complexity theory and not lawn mowers. And it goes on for over 200 pages.
Melanie Mitchell's "Complexity: A guided tour" is a far better book. Just get that one.
1 of 1 people found the following review helpful.
Great First Book in Complexity Science
By William A. Reed
Complexity theory can be a difficult topic to learn and there is a wide body of literature with varying descriptions of what complexity means. Johnson's book is a great starting point for many readers because it is conversational in tone, free of complicated equations, covers a wide range of topics and does not assume a prior knowledge of complexity theory.
Johnson begins with a patient and detailed introduction to complexity and then introduces the role of disorder to build the groundwork for defining chaos, taking care to explain that chaotic does not equate to randomness when defined in scientific terms. His description of the eight key components of complexity (p. 15) are particularly valuable insights for those new to the topic.
An important feature of this book is Johnson's ability to make certain core concepts of complexity science clear to his readers. Examples include topics such as "pockets of order" (p. 21), "strange attractors" (p. 46), and "anti-crowds" (p. 72). Yet, Johnson's extended example of disordered files and filing cabinets quickly grows tedious. Nevertheless, for those who can endure the details, the example provides an effective way to explain some rather obscure concepts in complexity theory (e.g. strange attractors, chaos).
Johnson also articulates a very clear explanation for the formation and function of fractals as emergent outcomes in certain complex systems. This unique approach to explaining fractals is especially valuable for non-mathematicians who are curious about their relationship to system outcomes. Yet, because many people are confused by the role of fractals in complex systems it would have been helpful for the author to contrast the types of systems where fractals are, and are not expected to form. There appears to be considerable confusion about this in the business community and the popular press, especially related to organizations as complex systems.
Another topic which often seems confusing to those learning complexity is the role of feedback, especially in the organizational context where information is the medium of exchange that alters the system. Johnson depicts a framework (p. 26) of how feedback can influence complexity and provides order to a system, but fails to emphasize how feedback operates differently in a complex system, compared with a cybernetic system. He does indicate that feedback incorporates learning and memory into human dynamics but seems to suggest that feedback is the key ingredient that moves systems from order to disorder and back (p. 110). Johnson could be much clearer that complex systems don't experience feedback as a regulatory mechanism to maintain equilibrium as seen in more traditional dynamical systems. And that disorder or emergent outcomes in complex systems are also related to other mechanisms. This is conceptually important, because complex systems are generally "far from equilibrium", a characteristic that has deep implications for expected system behavior.
Overall, these are minor issues that don't mitigate the value of this excellent book, which represents an accessible and thorough treatment of complexity science at the introductory level. Lastly, don't overlook the appendix for an extensive annotated list of references and resources about complexity topics.
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