 | Simply Complexity: A Clear Guide to Complexity Theory |
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Product Description
What do traffic jams, stock market crashes, and wars have in common?They are all explained using complexity, an unsolved puzzle that researchers believe is the key to predicting - and solving-everything from terrorist attacks and pandemic viruses right down to rush hour traffic congestion. Scientists can predict shopping habits, patterns in modern jazz, and the growth of cancer tumors. Considered by many to be the single most important scientific development since general relativity.
- Amazon Sales Rank: #7619 in Books
- Published on: 2009-10-16
- Original language: English
- Number of items: 1
- Dimensions: .77" h x 5.22" w x 7.84" l, .61 pounds
- Binding: Paperback
- 256 pages
Features
- ISBN13: 9781851686308
- Condition: New
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Review
"A highly engaging and accessible introduction to complexity theory that will be of interest to a broad readership." -- Christophre Georges - Professor of Economics, Hamilton College
"An excellent introduction to complexity -- a branch of science that every one of us in our time should be aware of." -- Pak Ming Hui - Professor of Physics, The Chinese University of Hong Kong
"This is a wonderful book, simultaneously deep and highly readable. It provides unexpected insights into a wild array of subjects ranging from jazz to traffic jams to war." -- Michael Spagat - Professor of Economics, Royal Holloway College, University of London
'It's lucidly explained, engagingly written and constantly surprising: complexity made simple!' -- Philip Ball -- best-selling author of Critical Mass: How One Thing Leads to Another
"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." -- Choice
It's lucidly explained, engagingly written and constantly surprising: complexity made simple! -- Philip Ball -- best-selling author of Critical Mass: How One Thing Leads to Another
It's lucidly explained, engagingly written and constantly surprising: complexity made simple! -- Philip Ball best-selling author of Critical Mass: How One Thing Leads to Another
This is a wonderful book, simultaneously deep and highly readable. It provides unexpected insights into a wild array of subjects ranging from jazz to traffic jams to war. -- Michael Spagat - Professor of Economics, Royal Holloway College, University of London
About the Author
Neil Johnson is Professor of Physics at Oxford University, and is currently working at the University of Miami in Florida. He is also co-director of Oxford University's research collaboration into Complexity.
Most helpful customer reviews
76 of 81 people found the following review helpful.
By 42below
There seem to be an abundance of books that focus on simple questions like "why is the sky blue?" or "why don't penguins get cold feet?", I have always found these types of books interesting, but ultimately the answers are of little relevance to my everyday life where I turn on the news and am confronted with falling stock markets, terrorist attacks and the spread of the latest computer virus. Why do things like these occur, can we understand them and what do they have in common?
It is through answers to these questions and the explanations of everyday events that "two's company, three is complexity" really shines. Using the science of Complexity Johnson explains the underlying causes behind many of the phenomena we see in the world around us. Phenomena like traffic jams, terrorism, stock markets, the common cold and the growth of cancer tumours. Before I read this book I had assumed these things were too difficult to understand (without a PhD), or that they just occurred at random. However Johnson largely succeeds in explaining these phenomena using intuition, diagrams and good analogies. To his credit equations are kept to a minimum so the book remains very readable. That said I think that the real strength of the book lies in its ability to draw parallels and links between these seemingly disparate systems. I started to realise that the growth of a Cancer tumour was perhaps not so different from the movement of traffic on city streets, or that the price movements on international currency markets might be share many features with the spread of the common cold.
In reading this book I had a large number of Ah-Ha moments and perhaps that is why it is ultimately so enjoyable. It was as if a light bulb would suddenly appeared over my head as I read the explanations.
Summary
This book is an engaging tour through the new science of complexity, told in an addictive manner. Do yourself a favour and next time you are going on a long flight, ditch the B grade in-flight movie and read this book instead. You will come out with a new appreciation of the way our world works and you will never look at a traffic jam in the same way again :)
24 of 24 people found the following review helpful.
By Warren R. Grayson
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.
20 of 23 people found the following review helpful.
By Irfan A. Alvi
Complexity science is a broad field with vague boundaries, so no single book can cover the whole field in depth. In this book, Neil Johnson focuses on a definition of complexity associated with a particular class of computational models, and he describes these models and their resulting behaviors at a level suitable for the general reader (somewhat detailed descriptions, but essentially no formal math). He has a PhD in physics and has himself done considerable research on these types of models (see the references at the end of the book), so his knowledge in this area is fairly authoritative.
For Johnson, a complex system has the following characteristics:
(1) A population of multiple (at least three) interacting objects or "agents" which typically form a network. These objects may be very simple, but they don't have to be.
(2) Competition among the objects for limited resources. As part of this overall competition, there can also be local cooperation within the system.
(3) Feedback processes, which give the system memory and history.
(4) Ability of the objects to adapt their strategies in response to their history.
(5) Ability of the system to interact with its environment.
(6) Self-organization of system behavior, without the need for a central controller.
(7) Emergence of non-trivial patterns of behavior, including a complicated mixture of ordered and disordered behavior. This can include chaotic behavior, as well as extreme ordered behavior (eg, traffic jams, market crashes, human diseases and epidemics, wars, etc.).
Johnson gives many examples of complex systems, and a jazz band is among the most interesting of these examples (the jazz performance is the behavior of the system).
Here are some of the key results from the models he describes:
(1) Even if the objects comprising the population of the system are complicated and heterogeneous (eg, people), this variability tends to "average out" in a way that allows the objects to be modeled as being fairly simple and homogeneous (at least as a first approximation).
(2) Due to competition, the population of objects will often become polarized into two opposing groups (eg, bears and bulls in financial markets, opposing political parties, etc.). This competition tends to reduce fluctuations in the behavior of the system.
(3) It's sometimes possible to steer the behavior of a system by manipulating a subset of the system's objects.
(4) Network structure tends to make complex systems more robust.
(5) The overall behavior of a system, and the ability of individual objects in the system obtain resources, depends on both the amount of available resources and the level of connectivity (network structure) between objects. When resources are only moderate, adding a small amount of connectivity widens the disparity between successful and unsuccessful objects, whereas adding a high level of connectivity reduces this disparity. By contrast, when resources are plentiful, adding a small amount of connectivity is sufficient to increase the average success rate and enable most objects to be successful. These patterns are consistent with what I've observed in the competition among engineering firms over the years (including during the current recession, a time of reduced resources).
(6) The behavioral outcomes of complex systems often follow a power law distribution, with smaller events being most common, but with extreme events also occurring more often than one might expect.
One of my main motivations to read this book was to get insight into how malignant tumors might be modeled as complex systems, with the hope that such models might provide clues regarding more effective ways to treat cancer. I was pleased to see that Johnson does discuss cancer at several points in the book, but I was disappointed to find that his discussion of cancer modeling is relatively superficial. Nevertheless, I'm firmly convinced that cancer is best modeled as a complex system, so I believe that much more research along these lines is (urgently) needed.
Overall, I do recommend this book. Johnson is qualified to write it, and it works well as an easily understood introduction at a level of detail suitable for general readers. However, again, keep in mind that the scope of the book is fairly narrow, so many important topics aren't mentioned at all. As a result, the book provides a good understanding of some of the trees in the forest of complexity science, but not much sense of the overall forest. For a broader introduction to complexity science, I recommend Complexity: A Guided Tour by Melanie Mitchell.
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