---
product_id: 12707648
title: "Complexity: A Guided Tour 1st Edition"
brand: "melanie mitchell"
price: "€ 62.71"
currency: EUR
in_stock: true
reviews_count: 9
url: https://www.desertcart.pt/products/12707648-complexity-a-guided-tour-1st-edition
store_origin: PT
region: Portugal
---

# Complexity: A Guided Tour 1st Edition

**Brand:** melanie mitchell
**Price:** € 62.71
**Availability:** ✅ In Stock

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- **What is this?** Complexity: A Guided Tour 1st Edition by melanie mitchell
- **How much does it cost?** € 62.71 with free shipping
- **Is it available?** Yes, in stock and ready to ship
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## Description

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## Customer Reviews

### ⭐⭐⭐⭐⭐ 







  
  
    Head-and-shoulders the best introduction to complex systems theory around
  

*by D***D on Reviewed in the United States on July 24, 2016*

I'm a philosopher of science specializing in the foundations of complex systems theory, and this is absolutely the best comprehensive introduction to the field that I've come across.  Mitchell is a computer science professor, as well as part of the Santa Fe Institute, so she's absolutely a reliable source on this topic. The book is extremely accessible for someone with very little background in dynamical systems theory or higher mathematics, and despite being mostly non-technical, does a good job actually articulating the central problems and concepts clearly without sacrificing precision or accuracy.  It's a wonderful overview of the field, and I highly recommend it to anyone who is curious about what the hell a "complex system" is, why they're worth studying, and how science is learning to deal with them.  Anyone interested in where science (and philosophy of science) will be headed during the 21st century should pick this book up: the study of complex systems is poised to be the next "big thing" (or paradigm shift) within the natural sciences, and it's relevant to a really mind-boggling array of contemporary scientific, social, political, and philosophical problems.

### ⭐⭐⭐⭐ 







  
  
    Mitchell has a talent for explaining difficult material
  

*by A***1 on Reviewed in the United States on January 26, 2020*

In “Complexity”, Mitchell utilizes her talent for explaining difficult material.  She also seems wise, objective, humble despite her qualifications.  Whenever possible she uses simple, concrete examples to get her points across.  Ironically, the one subject where the book almost totally failed me was in the explanation of an AI computer program to generate analogies, Mitchell’s Ph.D. thesis subject. As Mitchell observes, “what we might call modern complex systems science is, like its forebears, still not a unified whole but rather a collection of disparate parts with some overlapping concepts.”  A key concept is the complexity that can arise from simple rules.  In fractal geometry a simple rule is applied repeatedly.  In the behavior of ants, complex, seemingly purposeful behavior arises from each ant following a simple set of rules, but in endeavors like foraging, only probabilistically.  This is typical whether it is ants foraging or the immune system combatting infection; many agents are working in parallel, and the most likely paths are followed the most intensively, but with some probability less likely paths or solutions are tried.  Genetic algorithms, which are heuristics for solving problems that cannot be solved by mathematical optimization, also work probabilistically, combining what have been the most successful solutions in each iteration with some chance of trying what are likely to be unsuccessful variants, thereby avoiding finding only local optima. Many subjects, such as neural connections in the brain, can be modelled as networks, embodying common concepts.  For example, often many nodes are connected to “nearby” hubs, which then provide longer connections to more distant hubs.  The distribution of the number of links to each node can often be approximated by a power law. Mitchell uses a simple equation to illustrate chaos.  For certain values of the equation parameter, successive iterations of the equation are supersensitive to the initial value of the input x, and generate a string of outputs that appear to be random numbers, whereas for other parameter values, the string of outputs converges to a single point, or oscillates between a fixed number of points.Mitchell often illustrates concepts by using biology.  I was surprised to learn that the eyes in many different creatures, humans vs. octopi, may not illustrate convergent evolution, but all start with the same critical gene – if a mouse version is implanted into a fruit fly leg during development, you get a fruit fly eye on the leg.  Conversely, not only is there not a single exponent for how metabolic rates vary with animal mass across all animals as Mitchell discusses, but the metric to examine is not resting metabolism, but maximum metabolic rate,  for that is what is constrained by blood supply (cf “Power, Sex, Suicide: Mitochondria and the Meaning Of Life” by Nick Lane).

### ⭐⭐⭐⭐⭐ 







  
  
    This is a tour.
  

*by S***A on Reviewed in the United States on December 11, 2014*

This is not an encyclopedia. To appreciate it, you will have to spend just a little time considering what Dr. Mitchell has to present. While no math is required, it is helpful to know some. No science background is required, but it is beneficial to have had at least a couple of classes in science.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.

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*Last updated: 2026-05-01*