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Emergence from Chaos to Order

john h. holland

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"Emergence" is the notion that the whole is more than the sum of its parts. John Holland, a MacArthur Fellow known as the "father of genetic algorithms," says this seemingly simple notion will be at the heart of the development of machines that can think for themselves. And while he claims that he'd rather do science than write about it, this is his second scientific philosophy book intended to increase public understanding of difficult concepts (his first was Hidden Order: How Adaptation Builds Complexity). One of the questions that Holland says emergence theory can help answer is: can we build systems from which more comes out than was put in? Think of the food replicators in the imaginary future of Star Trek--with some basic chemical building blocks and simple rules, those machines can produce everything from Klingon delicacies to Earl Grey tea. If scientists can understand and apply the knowledge they gather from studying emergent systems, we may soon witness the development of artificial intelligence, nanotech, biological machines, and other creations heretofore confined to science fiction. Using games, molecules, maps, and scientific theories as examples, Holland outlines how emergence works, emphasizing the interrelationships of simple rules and parts in generating a complex whole. Because of the theoretical depth, this book probably won't appeal to the casual reader of popular science, but those interested in delving a little deeper into the future of science and engineering will be fascinated. Holland's writing, while sometimes self-consciously precise, is clear, and he links his theoretical arguments to examples in the real world whenever possible. Emergence offers insight not just to scientific advancement, but across many areas of human endeavor--business, the arts, even the evolution of society and the generation of new ideas. --Therese Littleton

274 pages, Paperback

First published January 1,1998

This edition

Format
274 pages, Paperback
Published
March 16, 2000 by OUP Oxford
ISBN
9780192862112
ASIN
0192862111
Language
English

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john h. holland

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Rating(3.4 / 5.0, 16 votes)
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16 reviews All reviews
Profile Image for Kimberly .
shiotanagisa1515
★ ★ ★ ★ ★
April 16,2025
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J. Holland explains here "emergence": how patterns persist in complex adaptive systems (CAS). He starts with a general discussion about models, follows with a model of the checker board game, and gradually introduces neural networks. He then presents generative constraint procedures (GCP), a way to describe these CAS, which while being formal, remain accessible—at least I followed. After a discussion reductionism, he concludes with the current status and future of research on the topic.

I find this book much broader than Hidden Order: How Adaptation Builds Complexity. I found the presentation of the checker game and of the neural network very clear, and yet deep. I also appreciate the very nuanced discussion about reduction and levels. I think this a very good reference on CAS: I found this text much more accessible than others such as Complex Adaptive Systems: An Introduction to Computational Models of Social Life for instance. I recommend it, definitely.
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200765
★ ★ ★ ★ ★
April 16,2025
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I wouldn't recommend reading this book because I think it's outdated. But for the ones very interested in complexity and emergence, this is a nice reflexion from the pioneer of the field. State, action, transition function, agent: the basics of modelisation used everywhere. I still found it better than the one he wrote before (Hidden Order), but I give less stars because it's more niche.
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Orderer
★ ★ ★ ★ ★
April 16,2025
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Typically excellent work from Holland. Here are a few general excerpts:

We only know that having a familiarity with several "nearby" disciplines, when the target does not fit well within an established discipline, will enhance the possibility of a source --> target transfer. The perception of what's "nearby" is a part of that still mysterious trait we call insight. (p. 213)

At a deeper level, our abysmal ignorance of most aspects of cognition presents a serious deterrent to the understanding of emergence. (p. 233)

The largest question Holland wants to answer goes like this: "How does the central nervous system select relevant pieces from the never-ending, perpetually novel torrent of sensory information it receives?"

We're only millimeters closer to answering that question than we've ever been. Once we're a few meters closer, we can start working on consciousness.
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pastelwishing
★ ★ ★ ★ ★
April 16,2025
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Good book for AI and software agents: This is a good book for people interested in Artificial Intelligence and Software agents (especially reactive agents). The book gives examples of emergent behaviours in the world. An interesting read.
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Bella-desu
★ ★ ★ ★ ★
April 16,2025
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Very good for anyone interesting in AI and emergence phenomena in general
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whyisthis
★ ★ ★ ★ ★
April 16,2025
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We never quite got to the order part except an imaginary one based on leaps of imagination, flights of fancy, and a slavish devotion to any scientific sounding theory that supported the author's thesis. The whole is greater than the sum of its parts, but you don't need this kind of leaping to conclusions, to call anything that suits a manifestation of emergence and to simply ignore anything that doesn't support the theory seems to be a bit intellectually dishonest. Although, in this case I would just suspect the author actually believes that his theory can predict outcomes for complicated relationships, one would guess from supply chains to military actions. But, I am no more convinced than I was when I began. Don't waste your time.
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Fa_Solano
★ ★ ★ ★ ★
April 16,2025
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In Emergence: From Chaos to Order, Holland takes a complicated and difficult topic and attempts to make it accessible to the non-specialist. His writing is clear and succinct but is still a challenge for those not familiar with the area, especially computer programs. Despite the challenge, the book is well worth the effort. Holland draws largely from a consideration of games (especially checkers and chess) and simple neural nets to build the concepts in offer of models which demonstrate emergence. Following his steps supports several insights into many phenomena that present emergence, cognition being a very important one. He concludes the book with a "closing," which in his own words is both a kind of summary conclusion and a sense of where to go from here ("coming closer"). I found the chapter immediately proceeding his closing (on metaphor and innovation) particularly engaging.
The book includes a bare minimum of mathematics, many figures (diagrams), and additional information/detailed examples in insets in each chapter. There is also a section of references and an index.
I recommend the book as a basic but bit involved introduction to emergence, especially useful for those interested in programming, artificial intelligence (AI), cognition, genetics, and evolution.
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