Or what ants, neurons, cities and software have in common.
It is not easy to find a book that helps us to understand what the Internet means for the transmission of knowledge at a global level, because everything that is published daily on this subject has an expiration date, they are punctual data, and do not go into the background of the mechanisms that move this and other phenomena, increasingly common, phenomena that have in common a self-organized structure as opposed to the hierarchies to which we are accustomed. Emerging Systems was written in 2001, and in spite of this, most of the topics dealt with in the book are not covered in the book. are still in force todayAmong other things because the author tries to make the phenomenon of the emergence of systems understandable with examples as disparate as: an anthill, the brain or the Manchester of the 19th century.
Steven Berlin Jonson is an American popular science writer. He has worked as a columnist for magazines such as Discover and Wired, and was a founding partner in the ezine Feed, and since 2006 has run the Outside-in community.
Emergent Systems is a popular science book that explains phenomena that we know but do not understand, such as the social networks of the Internet or the way in which neighborhoods are created within large cities. The explanation for these types of systems must be sought from the bottom up instead of trying to see in them a hierarchical structure; the definition of an emergent or bottom-up system is one that is not controlled by a specific element or coordinator.
The author draws on various examples from zoology, programming and urban planning to illustrate, and devotes an entire chapter to debunking the myth of the queen ant. In ant colonies, far from what the myth of the queen ant claims, decisions are made individually by each ant based on a prior reading of the pheromone level of its environment. If an ant detects that the frequency of foraging ants is low (it has not crossed paths with any ants all morning), it will believe that the number of foraging ants is low and will therefore start foraging. Of course, this is a simple example to explain a very complex subject, but valid to introduce us to an exciting world about these self-organized systems.
In the last part of the book we go deeper into computer science, especially in evolutionary software, and it is there where the reader starts to find it difficult to follow the storyline, both because of the technical language used and because of the eight years that have passed since its publication, since computer science has changed a lot during this time.
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