The Engine of Complexity: Evolution as Computation

by John E. Mayfield

The concepts of evolution and complexity theory have become part of the intellectual ether permeating the life sciences, the social and behavioral sciences, and, more recently, management science and economics. In this book, John E. Mayfield elegantly synthesizes core concepts from multiple disciplines to offer a new approach to understanding how evolution works and how complex organisms, structures, organizations, and social orders can and do arise based on information theory and computational science.

Intended for the intellectually adventuresome, this book challenges and rewards readers with a nuanced understanding of evolution and complexity that offers consistent, durable, and coherent explanations for major aspects of our life experiences. Numerous examples throughout the book illustrate evolution and complexity formation in action and highlight the core function of computation lying at the work's heart.

Genres: Science, Nonfiction, Evolution

416 pages, Hardcover

First published June 1, 2013

Reviews

[John · Rating 2 out of 5]

I found myself unable to finish this book in the time it was available to me from my local library, and was disappointed with the parts that I made it through. Coming from a computer science background with some experience in genetic algorithms, I was concerned by the author's imprecise use of computer science terminology and concepts; while he clearly knows biology, this cast some doubt on his statements about other areas. This is particularly problematic because the book is extremely broad in scope, going well beyond the fields in which the author seems expert. Some chapters were very speculative; while I think Mayfield's central premise (that evolutionary methods are an explanation for much of the complexity we observe) is plausible, in several cases Mayfield lacks any concrete evidence for application of this theory to particular fields and ends up arguing very softly / philosophically; having been introduced to the premise of evolution as computation and complexity source, these speculative arguments could have been mentioned in passing or left to the reader rather then receiving whole chapters. The writing style is fairly verbose and repetitive, which detracted from the readability; the book could've used an aggressive editing pass and a shorter pagecount. I am forced to conclude that I am probably not the target audience ("too indirect, insufficient rigor"), but I am also unable to determine just whom the target audience is. Students of biology will likely suffer from the repetitive style. That the first third of the book spends a fair bit of ink citing Dawkins and countering creationist sentiment in uninspiring ways is likely to alienate believers and atheists alike (for boredom in my case).

All that aside, I did find a few useful details about biological evolution which I may be able to apply, about one per chapter. The self-assembling nanotiles he mentioned were cool, and mutation rates per transcription as a function of genome size were unexpected and very interesting. I regret that these wonder-inducing details were so infrequent.

[Mark · Rating 4 out of 5]

Although there is probably nothing in here that you haven't seen, if you work in the life sciences; this is a very nice, clear and persuasive presentation of evolution, evolutionary systems and evolutionary-like systems. The author applies these concepts to the immune system, brain function, and science itself. The computer code examples are especially satisfying.

[Dan Wigglesworth · Rating 3 out of 5]

By the time had I finished this book, I was very happy I did, though at one point I had put it down and said, "I'm not going to finish that!"

Mayfield's thesis is extraordinary and therefore demands extraordinary explanation. As a result, the book is sometimes an exciting read. However, he struggles a little with the computational aspects of his explanations. And that is a huge stumbling block for a book which explains evolution in terms of computation. As Mayfield writes, "(the field of computer science) may be most fundamental to the nature of reality." It must be frustrating to the author to find that expertise in biology leaves one without the tools to get to the fundamental nature evolution. But to his credit, he struggles through it anyway and the book turns out to be a satisfying read.

Mayfield tells a particular vignette that will always stand out in my imagination: the story of how a new bacteriophage is reconstructed. I am still surprised that I had never heard of this before and I'm grateful for having found it in Mayfield's book.

[Ogi Ogas · Rating 2 out of 5]

My ratings of books on Goodreads are solely a crude ranking of their utility to me, and not an evaluation of literary merit, entertainment value, social importance, humor, insightfulness, scientific accuracy, creative vigor, suspensefulness of plot, depth of characters, vitality of theme, excitement of climax, satisfaction of ending, or any other combination of dimensions of value which we are expected to boil down through some fabulous alchemy into a single digit.

[Hans · Rating 5 out of 5]

基于对熵的理解，我们知道基因核心特质，变异是怎么回事。
基于进化，我们知道复杂性来自于变异。
基于信息， 我们知道事物来自于指令（基因、蓝图） 。而这，区分万物为两类。

由此，二元论已死，物理和心灵之墙开始坍塌，新的世界观重生。

[Jonathan Jeckell · Rating 4 out of 5]

An interesting look at evolution as an information processing algorithm, which accumulates complexity and information by generating variation, making copies with small changes (may or may not be random), selecting against a consistent criteria, and repeating. This process gradually accumulates more and more information about how to be successful in its environment. This framework examines life, the immune system, human social systems, the evolutionary computer algorithms, and the human learning process as evolutionary systems. It also shows how certain other things, like the structure of the brain, use parts of this mechanism, but not all of it. Particularly interesting bits were how this process can optimize against a static requirement (like environmental conditions), or fall into a competitive cycle of co-evolving against other evolving agents (and the Red Queen effect). He also discussed how the process can work with purposeful changes and design, rather than random variation (the latter would be "natural selection).

[Flavio Barbosa · Rating 5 out of 5]

I was interested in a description of current artificial evolution computer research and stumble on this book. I bought it knowing it was not quite about it but decided to give it a try. I am grateful for that. Outstanding job. It is not easy, but it is highly recommended for anyone trying to understand this life that we are all going through.

[CR · Rating 4 out of 5]

Interesting stuff

[Felix Sosa · Rating 4 out of 5]

A great read. A perfect introduction to the world of complexity and it's vast implications in layman's terms.

[Micah Redding · Rating 5 out of 5]

Helped clarify a lot. Fortuitously dovetailed with NonZero.

[Muyun Du · Rating 5 out of 5]

I read the translated version of this book in Chinese in a provincial library. I would go so far and say that the reading experience was revealing, even enlightening. So many vivid(and graphical) examples——now evolution just makes sense to me, instead of being some obscure memory of the juxtaposition of pics of chimps and homos in the textbook.

The following lines are from the epilogue to Clarel, Herman Melville's epic poem. He had actually been to the Galapagos as a sailor. These words show his struggle as a Calvinist, but anyone who consider free will vs fatalism a question would find resonance in them.

If Luther's day expand to Darwin's year,
Should that exclude the hope — foreclose the fear?

I would say at least for me, The Engine of Complexity has largely foreclosed my doubts about my origin, but luckily and unluckily, I have yet to find my purpose. The kind of purpose that the cyanobacteria that oxidized the atmosphere and the asteroid that wiped out the dinosaurs didn't need to have.

Enough with the Schmaltz, I want to share a funny thought I had reading the book. When the author complained about the scientific illiteracy of Americans in the preface, there is actually a simple explanation: science memes aren't competitive enough. For instance, the mormons institutionalized transmission, requiring young mormons to preach, hand out books for free and knock on your door and chat with you (sometimes annoying, but still friendly, and free) while this book per se costs $40. Of course there is Khan Academy and Cousera and MIT Opencourseware, they are all free but they don't reach to you, at least not like the mormons. So it actually makes sense that some people believe in Upstate New York as a holy land but disregard radiometric age-dating evidences. I would call this instance a meta-meme.