Complexity: A Guided Tour,   ISBN:9780195124415

Customer Rating: 

I know the title says "tour" but even for that, the material is very light. The author has done the field a disservice. If this book shows anything it shows how science is basically lost and going nowhere. Let me be specific and give an example: The author asks the question "How can simple biological mechanism result in a complex world?". You would think she would submit a reasonable answer? The "answer" is very weak along the lines of "scientists now think they were all wrong before and *maybe* it is this non coding DNA strings that turn genes on and off that can explain the added complexity". Really? Maybe. This kind of, science, is becoming a religion on its own. As an atheist I am offended.

Customer Rating: 

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.

Customer Rating: 

Simply put, one of the most amazingly accessible and -- on the basis of some expertise coming into reading it -- accurate presentations of a massively complex technical subject that I've ever read.

As an experienced computer scientist, primarily with "von Neumann" machines, but also with some experience in connectionist architectures, her explanations of all material with which I *am* familiar are as economical and lucid as any I've seen. Her explanations of systems further afield from my comfort zones -- cellular automata, genetic algorithms, etc. -- have me feeling comfortable with my understanding of them in a way that no previous treatment has achieved.

I'm about to order her book on celluar automata, and at this point I'd buy (and recommend) anything she writes without hesitation. Scientists who are also excellent writers are rare as hens' teeth -- to use the title of a work by one of the few other hugely literate scientists, the late (and very much lamented) Stephen Jay Gould, who.

I don't know whether this niche constitutes a genre, but if so Mitchell is a master of the genre.

From a technical standpoint, Mitchell's Ph.D. adviser was Doug Hofstadter -- a pedigree that is quite evident. She's got me wanting to re-read Goedel, Escher, Bach -- no mean feat, since that's a huge undertaking.

If you have any interest in complexity, buy this book.

Customer Rating: 

Considero que es un excelente libro y ha superado las expectativas que tuve al comprarlo. La autora ha logrado desarrollar un tema difícil como la "teoría de la complejidad" y además hacerlo ameno y atrapante.
Lo recomiendo para todos aquellos que estén buscando a una guía para no perderse en los vericuetos de la complejidad.

Customer Rating: 

Melanie Mitchell is the protege of Doug Hofstadter, and who wrote the Copycat program that models analogy making in a toy world that formed the basis of Hofstadter's "Fluid Concepts And Creative Analogies: Computer Models Of The Fundamental Mechanisms Of Thought". I still don't know why this approach isn't used in collective intelligence programming, perhaps it needs a wider audience and less rigid ideas about machine intelligence.

In complexity, Mitchell takes us on a broad tour of the subject, covering all the major bases and interleaving the threads of biology and computation into an informative cloth of complexity. What makes this book stand out from teh others in it's class is how Mitchell shows the various threads come together. Biology is science that is full of phenomena that show remarkable complex behaviors based on interacting units and she provides a few examples - ant colony foraging, the immune system and metabolism. She shows how computational techniqes shed light on how these phenomena may be explained and how we might understand biology as computation.

For me the most interesting part is chapter 11 - "Computing with Particles". She shows how a genetic algorithm evolved cellular automata rule set may be propagating information in its world. While the example is simple, it just begs for more study in different systems and seems like a very interesting idea to follow in real networks, like brains. I couldn't help but wonder if this was the missing model needed for Calvin's excellent "The Cerebral Code: Thinking a Thought in the Mosaics of the Mind".

Mitchell does her readers a great service in not just covering the broad range of topics, but also explaining where the science of complexity (if there is indeed one) fails and where key ideas are controversial and why. In this regard, her discussion of Kauffman's seminal "Origins of Order" is outstanding, highlighting the problems of his approach.

If you want a readable, thought-provoking book on complexity and computation, this is the one to buy. I found it unputdownable and read it in a single session.