- Tapa dura: 368 páginas
- Editor: OUP USA (28 de mayo de 2009)
- Idioma: Inglés
- ISBN-10: 0195124413
- ISBN-13: 978-0195124415
- Valoración media de los clientes: 1 opinión de cliente
- Clasificación en los más vendidos de Amazon: nº218.448 en Libros en idiomas extranjeros (Ver el Top 100 en Libros en idiomas extranjeros)
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Complexity: A Guided Tour (Inglés) Tapa dura – 28 may 2009
Descripción del producto
She captures the excitement of research. (Ian D. Couzin, Science)
Reseña del editor
As science probes the nature of life, society, and technology ever more closely, what it finds there is complexity. The sophisticated group behavior of social insects, the unexpected intricacies of the genome, the dynamics of population growth, and the self-organized structure of the World Wide Web - these are just a few examples of complex systems that still elude scientific understanding. Comprehending such systems seems to require a wholly new approach, one that goes beyond traditional scientific reductionism and that re-maps long-standing disciplinary boundaries.
This remarkably accessible and companionable book, written by a leading complex systems scientist, provides an intimate, detailed 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. In this richly illustrated work, Melanie Mitchell describes in equal parts the history of ideas underlying complex systems science, the current research at the forefront of this field, and the prospects for the field's contribution to solving some of the most important scientific questions of our current century.
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I read many of the one and two star grumbles below before I posted this. Somehow, they missed the point of her book. The world is far more complex and fascinating than we imagined. She integrates birds, broccoli, social networks, earthquakes, and economic concepts by presenting some of the hidden common factors.
Is this complete? No. The field seems to be at a similar point to where the mathematics was before the birth of Leibnitz and Newton. On the other hand, you might suddenly see a connection no one else has. Here is an example. There is a similarity between the studies of cities, information theory concepts, and ants. Enjoy the exploration.
So I think it serves mostly to stimulate the imagination, if that's what you're looking for. But it doesn't persuade and doesn't do more than point in general directions.
However, along with Soft Systems Methodology, the hope of a science of complex systems seems to have eluded us; and it does not look now that we will ever get there. It book seemed a little over optimistic given that the quest had run its course and in retrospect the personal details seem no longer all that relevant.
So I was left a little disappointed as much by the subject as the exposition. Buts its worth a read just to see if you reach the same conclusions.
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.