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By Melanie Mitchell

What allows separately basic bugs like ants to behave with such precision and objective as a bunch? How do trillions of neurons produce whatever as terribly advanced as recognition? during this remarkably transparent and companionable publication, prime advanced platforms scientist Melanie Mitchell presents an intimate journey of the sciences of complexity, a extensive set of efforts that search to give an explanation for how large-scale advanced, geared up, and adaptive habit can emerge from basic interactions between myriad members. in response to her paintings on the Santa Fe Institute and drawing on its interdisciplinary concepts, Mitchell brings readability to the workings of complexity throughout a wide variety of organic, technological, and social phenomena, looking for the final ideas or legislation that observe to them all. Richly illustrated, Complexity: A Guided Tour--winner of the 2010 Phi Beta Kappa booklet Award in Science--offers a wide-ranging evaluation of the information underlying complicated structures technological know-how, the present examine on the vanguard of this box, and the customers for its contribution to fixing one of the most vital clinical questions of our time.

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Our schedule permitted only a short time to hear about the historical background, to visit some important sites, and to get a feel for the landscape and culture of the place, with translations provided from the native language when necessary. This book is meant to be a much expanded version of those lectures—indeed, a written version of such a tour. It is about the questions that fascinate me and others in the complex systems community, past and present: How is it that those systems in nature we call complex and adaptive—brains, insect colonies, the immune system, cells, the global economy, biological evolution—produce such complex and adaptive behavior from underlying, simple rules?

But more quantitative questions remain: Just how complex is a particular complex system? That is, how do we measure complexity? Is there any way to say precisely how much more complex one system is than another? These are key questions, but they have not yet been answered to anyone’s satisfaction and remain the source of many scientific arguments in the field. As I describe in chapter 7, many different measures of complexity have been proposed; however, none has been universally accepted by scientists.

Wait a minute! 01816 of a rabbit? Obviously in real life we cannot, but this is a mathematical model, and it allows for fractional rabbits. This makes it easier to do the math, and can still give reasonable predictions of the actual rabbit population. So let’s not worry about that for now. 4 and carrying capacity is doubled to sixty-four? The model tells me that, starting with twenty rabbits, by year nine the population reaches a value close to twenty-four and stays there. You probably noticed from these examples that the behavior is more complicated than when we simply doubled the population each year.

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