Melanie Mitchell

This book provides an intimate, highly readable tour of the sciences of complexity, which seek to explain how large-scale complex, organized, and adaptive behavior can emerge from simple interactions among myriad individuals. The author, a leading complex systems scientist, describes the history of ideas, current research, and future prospects in this vital scientific effort.

A Guided Tour

Complexity

Dana Kraft

I enjoyed the subject matter in this book even if some of it dragged a bit. The early chapters were best in my opinion. The couple of main lessons learned for me were the idea that reductionism is a bit of a fools errand. You can't always understand something just by breaking it down to its individual components. The second is the concept that a system includes (and may be defined by) it's ability to gather and process information. I also kept thinking about how some of these theories or concepts apply to macroeconomics. I've always had a 'reductionist' view of economics which seems to not really apply at the macro level. I'll be looking for books that try to apply some of this to the business world.

Safiya 

I guess that up until then chapter 5, concepts were abstract about complexity sciences notions and basic information. But if you're a neophyte you'd better read those chapters to grab the main essence of complexity sciences and its objectives.

The author teaches a famous introductive course on complexity in SFI (a MOOC on Complexity Explorer), I wasn't successful to enrol it in due time, but this book quite tackles all the chapters of the course.

The equations aren't hard to understand as she explains all the parameters bit by bit, and finds analogies to better illustrate the abstract notions.

And speaking of analogies, complexity sciences objective might be counterintuitive... It uses transdisciplinary tools and models to answer basic questions about LIFE.
It's very common in CS to find social scientists collaborating with biologists, mathematicians and computer scientists to understand a specific question: understanding evolution, collaboration patterns to be used in international affairs and political sciences... Or even understand markets..

In any case, this field may be recent compared to the classic sciences we know, but it has made a big difference in understanding today's world... As a matter of fact it has made some bold statements and suggested controversial theories too...

The ultimate objective of this science next to understanding how the world / globe / life works, is to find any contingencies among different fields... Ideally reaching a unified theory of everything... Rings a bell?

I think the philosophical framework of this emerging science is what interests me most, collaboration across fields in between fields where everyone's insight is welcome to help come up with answers... Some sort of democratization of research... 

I think this a good start before attending this year's Complexity Interactive seminars at Santa Fe Institute, we are set!

Update : Met Melanie on October 19th, 2020

Chris Aldrich

This is handily one of the best, most interesting, and (to me at least) the most useful popularly written science books I've yet to come across. Most popular science books usually bore me to tears and end up being only pedantic for their historical backgrounds, but this one is very succinct with some interesting viewpoints (some of which I agree with and some of which my intuition says are terribly wrong) on the overall structure presented. 

For those interested in a general and easily readable high-level overview of some of the areas of research I've been interested in (information theory, thermodynamics, entropy, microbiology, evolution, genetics, along with computation, dynamics, chaos, complexity, genetic algorithms, cellular automata, etc.) for the past two decades, this is really a lovely and thought-provoking book. 

At the start I was disappointed that there were almost no equations in the book to speak of - and perhaps this is why I had purchased it when it came out and it's subsequently been sitting on my shelf for so long. The other factor that prevented me from reading it was the depth and breadth of other more technical material I've read which covers the majority of topics in the book. I ultimately found myself not minding so much that there weren't any/many supporting equations aside from a few hidden in the notes at the end of the text in most part because Dr. Mitchell does a fantastic job of pointing out some great subtleties within the various subjects which comprise the broader concept of complexity which one generally would take several years to come to on one's own and at far greater expense of their time. Here she provides a much stronger picture of the overall subjects covered and this far outweighed the lack of specificity. I honestly wished I had read the book when it was released and it may have helped me to me more specific in my own research. Fortunately she does bring up several areas I will need to delve more deeply into and raised several questions which will significantly inform my future work.

In general, I wish there were more references I hadn't read or been aware of yet, but towards the end there were a handful of topics relating to fractals, chaos, computer science, and cellular automata which I have been either ignorant of or which are further down my reading lists and may need to move closer to the top. I look forward to delving into many of these shortly. As a simple example, I've seen Zipf's law separately from the perspectives of information theory, linguistics, and even evolution, but this is the first time I've seen it related to power laws and fractals.

I definitely appreciated the fact that Dr. Mitchell took the time to point out her own personal feelings on several topics and more so that she explicitly pointed them out as her own gut instincts instead of mentioning them passingly as if they were provable science which is what far too many other authors would have likely done. There are many viewpoints she takes which I certainly don't agree with, but I suspect that it's because I'm coming at things from the viewpoint of an electrical engineer with a stronger background in information theory and microbiology while hers is closer to that of computer science. She does mention that her undergraduate background was in mathematics, but I'm curious what areas she specifically studied to have a better understanding of her specific viewpoints.

Her final chapter looking at some of the pros and cons of the topic(s) was very welcome, particularly in light of previous philosophic attempts like cybernetics and general systems theory which I (also) think failed because of their lack of specificity. These caveats certainly help to place the scientific philosophy of complexity into a much larger context. I will generally heartily agree with her viewpoint (and that of others) that there needs to be a more rigorous mathematical theory underpinning the overall effort. I'm sure we're all wondering "Where is our Newton?" or to use her clever aphorism that we're "waiting for Carnot." (Sounds like it should be a Tom Stoppard play title, doesn't it?)
 
I might question her brief inclusion of her own Ph.D. thesis work in the text, but it did actually provide a nice specific and self-contained example within the broader context and also helped to tie several of the chapters together. 

My one slight criticism of the work would be the lack of better footnoting within the text. Though many feel that footnote numbers within the text or inclusion at the bottom of the pages detracts from the "flow" of the work, I found myself wishing that she had done so here, particularly as I'm one of the few who actually cares about the footnotes and wants to know the specific references as I read. I hope that Oxford eventually publishes an e-book version that includes cross-linked footnotes in the future for the benefit of others.

I can heartily recommend this book to any fan of science, but I would specifically recommend it to any undergraduate science or engineering major who is unsure of what they'd specifically like to study and might need some interesting areas to take a look at. I will mention that one of the tough parts of the concept of complexity is that it is so broad and general that it encompasses over a dozen other fields of study each of which one could get a Ph.D. in without completely knowing the full depth of just one of them much less the full depth of all of them. The book is so well written that I'd even recommend it to senior researchers in any of the above mentioned fields as it is certainly sure to provide not only some excellent overview history of each, but it is sure to bring up questions and thoughts that they'll want to include in their future researches in their own specific sub-areas of expertise.

Victor Gomez Estevez

Gran introducción a los sistemas complejos, bien explicado y con suficiente profundidad

Complexity A Guided Tour

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