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If you are coming to this subject from an unrelated maths or physics field and looking to explore complexity and how it appears in Nature, this book may be perfect for you. Unfortunately, as a biochemist, I found the biology chapters far too basic and the maths ones far too advanced. I worked hard at it and managed to get my head around most of the tougher chapters, but beware biologists looking for an easy read - if you aren't in the mood for some hard thinking, this may not be the book for you!
I got this on the basis of a recommendation by Cosma Shalizi. Cosma Schalizi is usually a lethal critical intelligence, but he is too kind to his friends. More seriously, the editors at Oxford, who should also be Prof. Mitchell's friends, if only for the most instrumental of reasons, fell down badly on their various obligations, because this is simply not readable. I started into it looking forward to a relaxed survey of stuff that I more or less know, but was stopped dead by the prose inside a page or two. If you open it at random you will encounter sentences (in this case, in fact, even a paragraph), like
'The DNA of a viable organism, having many independent and interdependent regularities, would have high effective complexity because its regularities presumably require considerable information to describe.' (p.99)
'Complexity' is 300 pages of this. I really did open it and put my finger down to find this example, I didn't search it out.
I will live with writing like this if (a) I have no alternative, and (b) someone is paying me a lot of money; i.e. if I am reading a commercial software manual. I won't live with it if I am reading an actual real book aimed at an elective audience.
I don't really blame Prof. Mitchell, who is clearly enthusiastic and learned, but on the evidence has no idea how to write; I do blame OUP, who should have gently told her so, and taken appropriate action before this went to press.
Another (harsher) reviewer states "I felt like she was writing for a high school audience, or maybe college freshmen, and I suppose the book might work for that crowd." This is almost verbatim what my assessment was after I finished the book. The breadth and bland but inviting style might make this a very good book for a young person who is interested in the subject, who might use this as a jumping-off point into more specific and deeper work. As an up-to-date survey of the field for the technically-trained reader who has some previous knowledge of the subject, it leaves a lot to be desired in cohesiveness, pith, and style. The one thing that will probably stick with me is the author's addressing of the prior systems-theoretic disciplines of cybernetics and general systems theory at the very end of the book, and (to me) the unsuccessful distinguishing of current complex systems approaches from these. I was left with the impression that the current iteration has uncovered more suggestions of general systems principles, but we remain far (nearly as far?) from a predictive science of complexity.
This book is good, but it is not great. The first 5 chapters (maybe 8 if you were a overachiever) are just a review of basic concepts that most of us learned in high school. From there, the book reads more like an article into the then current field of complexity. The information presented is enough to spike your curiosity, but not enough for you to be able to understand or recognize complexity in either the abstract or the applied sense. Again, this is fine for an introduction, but you'll probably want to go further.
The problem that I have with this book is the author's method of explaining things, which is ironically somewhat complicated or difficult to understand at times. For example, when things such as a Turing Machine or Von Neumann's self-replicating code are being explained, the author unnecessarily makes things harder than they need to be. The Turing Machine could more easily be explained with a straight-forward arguments (proofs) similar to the way mathematical theorems are presented. A simple diagram with step by step deductions is much easier than reading a long list of prescriptive/instructional text. Similarly, the pseudo-code used was very awkward. It would have been much easier to just explain what recursion, procedures, decision making, etc. Basically, the things anyone would usually what you learn in the first few chapters or quick introduction in any programming language.
The book brings a reasonable overview about some brilliant scientists and also discuss how the nature (human body) is able to manage cells attacks and their amazing globules mutation, beyond of this, how the economic market is action driven by the majority, how the ants are randomically and at the same time focused and still interesting concepts about the complexity of the systems and colonies. On the other hand treats the topic in a non so interesting way showing a game logics and its probability. It is understandable that the book came from the author doctorade thesis but I think the game chapter is not written in a enjoyable manner. I think it could be better elaborated to be nicely swallowed by the readers. The book begining is much better than its end, you become very excited with the begining but frustrated with the end.
I liked this book in many ways and it told a really important story. But I found some parts of the book frustrating. At times it lost it's way a little, which was a pity because the information contained in the book was really valuable. There were some parts that were a little too repetitive and some parts a little too emotive. I would recommend this book because I think it's subject matter is very important and I really got a lot out of it. I just thought it could have been a little better written. I would definitely buy it again and I am pleased to have read it.
I purchased this book for a class and tried to use it in the analysis of complex adaptive systems, a field of study in public administration. Being an engineer at heart, I found the book excellent reading. But while trying to apply some principles of complexity to human organizations, I found that Dr. Mitchell could have researched a bit further and gotten outside the scientific realm. One example is to examine the origins of CALFED, an experiment in California to coordinate the needs of the few water providers and many users. There are examples of emergent behavior and non-linear or positive feedback mechanisms at work. Another area of active research is innovation networks. Innovation per Chesborough is theorized to occur in organizations at the boundary between chaos and equilibrium. But above all, Stacey's 1995 article in the Strategic Management Journal highlights many interesting points about complexity and organizational theory. The book on complexity theory and institutions, I suppose, has not been written yet.
While I enjoyed much of this book - ranging from its computational models to its description of some absolutely amazing complex systems - ultimately I found it frustrating that while the author would, near the end of the book, admit that "the degree of complexity in biology is only beginning to be fully appreciated", she would also work so hard to reassure readers that natural selection was an adequate root cause explanation for how such systems have arisen.
I would have appreciated the book more if it had focused primarily on the topic of complexity in natural systems and the math and computer models she's obviously strong in, but without attempting to segue into the religious aspects - that despite how poorly we understand the many breathtakingly complex systems that surround us (or which we are made up of!) that it's still indispensable that we have the faith to attribute the origin of these systems to the inconsistent and poorly understood mechanisms of natural selection.