John Holland argues that understanding the origin of the intricate signal/border hierarchies of these systems is the key to answering such questions. He develops an overarching framework for comparing and steering cas through the mechanisms that generate their signal/boundary hierarchies. Holland lays out a path for developing the framework that emphasizes agents, niches, theory, and mathematical models. He discusses, among other topics, theory construction; signal-processing agents; networks as representations of signal/boundary interaction; adaptation; recombination and reproduction; the use of tagged urn models (adapted from elementary probability theory) to represent boundary hierarchies; finitely generated systems as a way to tie the models examined into a single framework; the framework itself, illustrated by a simple finitely generated version of the development of a multi-celled organism; and Markov processes.
Thid is a good book but not quite satisfying. Holland is among those who made the most influential intellectual contribution to complexity science. I love his first genetic algorithm book to death. This review is entirely personal, so it might not reflect the greatness of this book due to the limitation of my own knowledge in this field and insufficient reading of his previous works.
I think the overall goal, or at least one major goal, of this book is to articulate his own picture of space. We are trying to figure out what's going on in this world, but first we need to decide what *is* the world. A 3D Euclidean space is intuitively comfortable but it is not a helpful construct to represent events, especially the relation of events. The tagged urn system discussed in this book can be an good example of what Holland think is a more meaningful construct of space.
Spaces, or Urns, here are autonomous, or say self-centered, or say relativistic, but interactive. The thing I like the most about tags is gives a general and natural description of the hierarchical systems in nature. I would call it peudo-hierarchy, since there are in fact only sequences, but no absolutely high or low, or say up stream or down stream.
This was really great in terms of its exploration, examples and so forth. Some parts are quite inspiring I think for any field, but Im also sure there is a lot I failed to absorb. Its the type of book I plan to re-read 5 years in the future and take in on a different level.
I was very disappointed by this book - I'd read the free sample on Kindle and it looked very interesting. Luckily, I got it from a library as I would really have hated to pay full price.
The premise is that you can model many aspects of complex adaptive systems (CAS's) using the mathematical formalism of Dynamic Generated Systems (dgs's (Holland's non-capitalization)).
He asserts that dgs's can model ecosystems, organisms, biological cells, economies, governments and more. Dgs's model the idea of an agent with a boundary that processes input signals and generates output signals.
He slowly builds up a more complex model but never provides enough detail, cherry-picks from hundreds of different examples while never providing a single convincing worked example.
He flips between levels (organism/species) too readily. For example, although he states that a species is an agent, a species does not have the same behaviour as an organism and does not even have a clear boundary.
He doesn't provide any worked examples of how his formalisms can model anything complex in the real world. His worked examples are of trivial problems; fair enough, but his claims at the end that they can be extended to the real examples that he cites fail to be convincing. It is all argument by weak analogy.
Since his models are simulations of CAS's, and there is no worked example to compare with a real world model, there is no way to know if they could be useful.
While I am usually sceptical about theories of everything of any kind, Holland's book is very good at explaining complex adaptive systems as models of seemingly unrelated things like genes, populations, economy and language.
The book reads like a college textbook with a matter of fact, deliberate tone. In each chapter a more complex and powerful models are introduced with more and more bizarre mathematical notations. The quirky way of modeling is why the book is a star off of perfect score. The other problem I see is that most of the examples are from system biology, and not enough from social sciences.
Author gave an overview and a quite deep exloratory investigation of the signal/boundary systems theory. There is a lot from complex adaptive systems. The theory is quite profound and interesting for those who want to understand origins of life, complex organisms, markets and economy. Though, the text of the book is quite abstract and sometimes hard to read.
Highly likely, in this book J. H. Holland tries to summarize his last thoughts on complex adaptive system in his old age. Could serve as a book for inspriations for anyone who are working in a field of CAS that is discussed in the book. The theorization looks too general to be immediately useful.
J. H. Holland presents another take on an overarching theory of complex adaptive systems such as financial markets, ecosystems, cells, or human organisations. The objective is to explain, or at least reproduce some of their key features including differentiation, specialisation, niche, etc. The author focuses here on signals and boundaries, that is one the mechanisms that could yields structures and communications between them.
I found the book interesting, but I did not really get how the many pieces fit together. The urn model, the learning classifier systems, etc., are all fascinating but still look like disconnected pieces to me. Besides, I am happy that I had already read two of the author's books, especially Hidden Order: How Adaptation Builds Complexity and Emergence: From Chaos To Order in particular. I found the text not really self-contained, especially when it comes to the Echo models.