5 comments about Inferring Phylogenies.

1. The book I bought is first printing version. Lots of typo inside..... I should correct them myself.-:(



2. As one would expect, the majority of this book deals with the various algorithms for phylogenetic analysis (such as the various versions of parsimony, distance based methods, and likelihood methods), but the book covers more topics that this. In particular, the book covers methods of tree comparison such as the KHT and SH tests, which I found particularly welcome because the current literature covering these tests often are rather opaque to those who haven't followed it since their conception.

   The only weak thing about about the book (besides the many typos, which should be fixed in the new printing anyway), is Felsenstein's rather acrimonious treatment of Bayesian methods, in which the Bayesian use of priors is criticized on philosophical grounds.

   I was annoyed by this not because I'm a card-carrying Bayesian (which I'm certainly not), but rather because I would have thought that Felsenstein of all people, whose primary opponents in the 1980's were the members of the philosophically-minded Willi Hennig crowd (who always claimed that parsimony was "philosophically right" even when it gave the wrong answer), would realize the futility of arguing scientific issues on philosophical grounds. Bayesian methods, as all scientific methods, will win or lose based on how well they work in practice, despite turgid philosophizing on both sides of the issue.




3. This book, although apparently containing everything, is written in a very opaque style which makes it impossible to simply read through. It probably is a good reference to look in for particular topics, but it is not at all usable as an introduction.



4. Inferring phylogenies was much anticipated by the large audience which has used Felsenstein's programs, and his website which reviews and categorizes applied tree building and population genetics programs.
   This book is very complete, and functions well as a reference book. It is not a book that would read from start to finish, and probably would not be the best text available for a general upper division course. We have used selected chapters for supplementary readings when appropriate in reading groups. However, due to its completeness, this would be one title that I would recommend that most people working with phylogenetics would require for their bookshelf.



5. This new explanation of phylogenetic methods contains a good discussion of the merits and potential failings of many of the methods currently used to study phylogenetics. It may be very good for computer science students, who have a better grasp of the mathematics. It may also be good for biologists well versed in biostatistics, who want to know why systematists use certain, less easily handled, analytical methods. However, it is very difficult reading for other scientists who do not fully understand the complex math presented in the text. It also does not give a concinct summary of the assumptions and failings of each method. The bottom line is that this book is good for experts who easily understand algorithms, but not good for students who don't have a good handle on such things.

2 comments about The Tree of Life: A Phylogenetic Classification (Harvard University Press Reference Library).

1. This book is truly a work of art in layout, design and presentation of line drawings and scientific content. It is one of the best scientific presentations I have seen and anyone remotely interested in this subject needs to check this excellent reference.



2. "The Tree of Life" is a thorough modern phylogenetic classification of life on this planet. This book is great for anyone interested in how different organisms are really related, from single-celled organisms up to humans and our close relatives. Anyone who has ever thought it strange that we should group turtles, crocodilians and dinosaurs together as "reptiles", but exclude birds (and mammals), will likely be interested in this book. The book is comprehensive, detailed, and well illustrated, and remarkably well-priced.
   
   This book covers the whole range of life on Earth, though primates and other mammalian groups are given far more thorough treatment than bacteria and archaeans. Each section provides a description of the distinguishing features of the relevant group, with examples of some of the members, information on the fossil record, and plenty of illustrations.
   
   The main drawback with such a work is, of course, that the field is changing rapidly and it is close to impossible to ever be fully up-to-date. Another minor, but slightly annoying, problem is that a number of errors have crept into the English translation, so, for example, "Pliocene" appears as "Pilocene" in many places in the book.*
   
   Nonetheless, the scope of "The Tree of Life", the detailed description and the abundant illustrations make this an invaluable reference work for those interested in biological classification.
   
   *Note: I assume that these errors are absent from the original French text.

5 comments about Resilience Thinking: Sustaining Ecosystems and People in a Changing World.

1. This is a great book. I've read several books on this topic, and so far, they have all had a similar issue: They are written by people who are scientists first, writers second. This book has two authors. One is a scientist and the other is a science writer. This made for a well put-together, understandable explanation of complex adaptive systems, which are what ecosystems are currently understood to be.
   
   The authors have done a few things to make the book great. First, they have broken the topic down into a set of subtopics, with one chapter explaining each subtopic. At the end of each chapter is a summary of important points so it's clear what the authors are hoping you get out of the chapter. Each chapter is then followed by a case study that is used to illustrate the ideas just covered.
   
   If you are looking for an introductory book on ecosystems and how humans affect their ability to maintain themselves, this is the book to read. The authors also provide several good resources at the end of the book if you would like to expand your knowledge further.



2. A MUST read for environmentalists. And for business, community and anyone willing to adapt the thinking to their situation. Brian and David have done a superb job in translating resilience theory and its close ties to complex adaptive systems. I have been looking for a book to recommend to my clients and students and this is it. I would also strongly recommend that the 'old guard' sustainability brigade have a look at this. The strategies that sustainability largely pursues are unsustainable. Resilience thinking is a more accurate path for us to head toward something that resembles sustainability. Well done.



3. This book is Latour's actor network theory in another guise, with the physicalization of Kuhn's paradigm shift thrown in for good measure. It is a very interesting book on an emerging way to look at environmental crises (note, not the environmental crisis. We seriously need local knowledge and local experience to manage each individual ecosystem).
   
   My major issues with this book are twofold. One is that it is not well written, though not altogether poorly written, you can simply tell when the science writer came in to jazz things up. Secondly, the authors spend a little too much time trying to convince the reader that resilience thinking is NEW, DIFFERENT, SUBVERSIVE, and the like. We get, on page 29, something that I just cannot stand: a little briefer than brief history of challenge to dogma. Galileo spoke out about the Copernican model (which was still perfect circles, Kepler had it right but Galileo ignored him) and the church shot him down. Darwin dared to say species change and the world exploded! Now, we, the humble new scientists bring you a new challenge to the dogma of ecology today. Give me a break! I would have thought a science writer on the team would have had the experience to leave out this trite nonsense. Just tell me about your idea and spare me the drama! Sorry, but poor history of science is a real pet peeve. :-)
   
   But either way, this is still an important book that should be read by ecology students, politicians, resource managers, and anyone interested in new ideas. The case studies are really informative and clear, and the message is properly urgent



4. This is a gem of an educational book. Mixing case studies with elaborating chapters on key concepts, it's as a good a volume as I have found for teaching undergraduates, graduates, and practitioners (farmers, factory managers, investors) the core ideas needed to restore a sustainable social-ecological system.
   
   Highlights for me:
   
   + Optemization is a false premise, simplifies complex systems we do not understand, with the result that we end up causing long-term damage.
   
   + Resilience thinking is systems thinking. I cannot help but think back to all of the excellent work in the 1970's and 1980's--the authors were simply a quarter century ahead of their time.
   
   + In a nut-shell, resilient system can absorb severe disturbance.
   
   + System resilience is affected by context, connections across scales of time and space, and current system state in relations to threshholds.
   
   + Fresh water, fisheries, and topsoil depletion are major failures.
   
   + Drivers of environmental degradation are poverty, willful excessive consumption, and lack of knowledge (from another book, I recall that changes to the Earth that used to take 10,000 years now take three, one reason we need real-time science).
   
   + Key concepts are threshholds and adaptive cycles. Adaptive cycles have four phases: Rapid Growth; Conservation; Release; and Reorganization.
   
   + Redundancy is NOT a dirty word (just as intelligence--decision support--should not be a dirty word within the United Nations)
   
   + Ecological networks cannot be understood nor nurtured with a tight linking and understanding of the social networks that interact with the ecological networks.
   
   + Subsidies are a form of social denial, as they subsidize unsustainable practices and prevent adaptation and change.
   
   + Lovely--absolutely lovely--chart on page 89 about time-scales of climate and natural disasters like major fires.
   
   + One size does not fit all--solutions for one social-ecological network, e.g. in the USA, will not be the same as for another, e.g. in Norway.
   
   + Diversity is the key to regeneration.
   
   + Governances must be able to see and act upon key intervention points.
   
   + A Resilient world would be characterized by:
   
   1. Diversity
   2. Ecological variables
   3. Modularity
   4. Acknowledgement of slow variables
   5. Tight feedbacks
   6. Social capital
   7. Innovation
   8. Overlap in governance
   9. Ecosystem services
   
   Within this small and very easy to absorb book one finds a great annotated bibliography of recommended readings, a fine reference section, and a very solid index.
   
   Other books that come to mind as complements to this one (limited to ten links by Amazon):
   The leadership of civilization building: Administrative and civilization theory, symbolic dialogue, and citizen skills for the 21st century
   Society's Breakthrough!: Releasing Essential Wisdom and Virtue in All the People
   Ecological Economics: Principles And Applications
   Natural Capitalism: Creating the Next Industrial Revolution
   Green to Gold: How Smart Companies Use Environmental Strategy to Innovate, Create Value, and Build Competitive Advantage
   Cradle to Cradle: Remaking the Way We Make Things
   The HOK Guidebook to Sustainable Design
   High Noon 20 Global Problems, 20 Years to Solve Them
   Pandora's Poison: Chlorine, Health, and a New Environmental Strategy
   The Blue Death: Disease, Disaster, and the Water We Drink



5. Brian Walker, Program Director Resilience Alliance and a scientist with the CSIRO. Canberra Australia, has, with the assistance of science writer David Salt, written the best and most straightforward work on ecological resilience entirely suitable for a wide audience of readers; activists, teachers, scientists from any number of disciplines, interested in gaining a familiarity with a study area that is of critical importance in this present world of catastrophe, forever changing with the calamitous onset of climate change and where stategies of adaptation are quite indequate mechanisms for survival in the white-water world we will have to navigate.
   
   It is not a scientific treatise but a work from which all interested readers will benefit substantially no matter what their background or credentials. This is a twentyfirst century production coauthored with a skilled science writer and a model for any NGO or scientific group who wish to influence and inform policy makers with something they can readiliy understand.. Resilience capability and building such capacity is perhaps the best, but still uncertain, way to buffer social-ecological systems--your everyday environment--from unpredictable, disastrous events and accompanying change. Adaptation and models based on orthodox science are unfortunately inadequate to meet such crises. I recommend this book to any concerned person no matter their level of understanding. They will find something new and enlightening here.

5 comments about The Structure of Evolutionary Theory.

1. I do not recommend you read this book unless you are an academic in the field and need to do so. Although I am unsympathetic with many of the ideas in it, the primary reason for my low rating is that the book was overlong and poorly written where it matters.
   
   I'll start with what I liked about the book. The first chapters were on the history of evolutionary theory, and it is here where Gould's principal strength as a popularizer comes through well. Although these chapters could have been more concise, and they were oriented towards backing Gould's ideas, I enjoyed them for the most part. The last chapters in the modern theory section on the importance of constraint were interesting, though they suffered heavily from Gould's style of discourse. I found the last pages of the book on the importance of contingency to be quite beautiful.
   
   The bulk of the book consisted of the material on punctuated equilibrium and Gould's hierarchy of Darwinian individuals. I had issues with the ideas themselves, but these are a distant second to what I felt about Gould's notion of an argument. Evolutionary biology is not a branch of philosophy and textual analysis should not, as Gould claims, "be pursued more often in scientific discussion." They are not done so, according to him, because of the "philistinistic culture of science." Molecular biology and mathematics are vital components of evolutionary biology, as much and perhaps more so than the incomplete fossil record. Gould gave lip service to molecular biology and much less respect to the now venerable and important discipline of population genetics - except of course when the results from these fields backed up his narrative.
   
   Gould's use of lawyerly argument, where verdict is truth, is the reason why he is rightfully disdained for opening the door to creation "science" in the debate on teaching evolution in schools. By stripping away hard science, and replacing it with metaphors, cartoons, and narratives, Gould took a rigorous theory, based firmly on empirical and deductive facts, and replaced it with a secular creation myth that is open to attack. Although this has made him the darling of what he calls the "literati", it is also what made him a bad scientist. The fact that he addressed modern Darwinism tangentially, chose instead to focus on Darwin's and others Victorian era writings, and rejected ideas because they didn't "feel right," didn't improve his standing with me.
   
   Gould's writing when it came to the science under debate was a nightmare. Intentionally or not, he constructed a complex hierarchy of nested, irrelevant tangents; tangents that were fragments within sentences, which were then tangents within paragraphs, which were in turn tangents within sections, ad nauseam. One of the most frustrating aspects of the book was that he refused to give a clear definition of what he meant by "punctuated equilibrium" until pg 1001: "We locate any revisionary status for punctuated equilibrium in its suggestions about the nature of stasis, and particularly its implications for attributing macroevolutionary phenomena to causes operating on the differential success of species treated as Darwinian individuals. Ordinary speciation remains fully adequate to explain the causes and phenomenology of punctuation." Others, such as Richard Dawkins, have done much on addressing this definition of punctuated equilibrium. My comment here is that it took so long to come to it, and up until this point Gould hinted at saltationist underpinnings to punctuated equilibrium, only to later decry and impugn the integrity of his critics for criticizing these alternative definitions.
   
   My main intellectual criticism was of Gould's hierarchy of Darwinian individuals. I thought this was fine as a phenomenological tool to describe macroevolutionary events, but Gould inverted cause and phenomena to claim that species selection is irreducible to gene or organism selection. His reason why? "Nonlinearities." Along with not knowing what the word "fractal" means, which he used quite a bit to mean either "self-similar" or "scales up", Gould thought "nonlinear" meant "hopelessly complex." His style of argument? Keep repeating the word irreducible until the reader breaks down. Gould was snidely dismissive towards the results of population genetics, but only addressed them directly in a (relatively) brief two page discussion where he claimed that they had to be invalid because population genetics models were able to explain both punctuated equilibrium (stasis followed by rapid change) and his cartoon notion of Victorian gradualism. Since Gould himself was clear that both are evident in the fossil record, it is strength, not a weakness, of a modeling system to be able to explain both.
   
   Although the ideas in the book did not all resonate with me, I would have recommended it if it was more clear and much, much more concise, since the ideas in it are an important part of the current discussion on evolutionary theory. But because of the poor writing in the important scientific parts of the book, and Gould's often unprofessional comments towards critics, I don't think this behemoth of a tome is worth your time.



2. Anything and everything by Gould is worth reading. He was aware that he was dying as he finished this book, and it bears the marks of an attempt to cram a lifetime of study and thought into one work. One feels that had he lived longer, the book would have been shorter. The extensive coverage of nearly forgotten figures who represent many examples of one type of opinion is not really necessary to make his points. The reader who is not a specialist will want to do a bit of skimming.
   
   But the length is a minor flaw. The book is an attempt to make all of his conclusions available to both the lay reader and his colleagues. Fundamentalists will read it as a critique of Darwinism; it's not. It represents an extension of Darwin to take into account all that the 20th century revealed about genetics, extinction, cladistics, emergent properties, and astronomical catastrophes. Hopefully it will stand as a monument to empiricism in the face of the new Dark Age that some see coming -- a time when we will forget not only what we knew, bu that we ever knew it.



3. In the weeks I spent poring over this landmark volume I don't recall any explanation of the social insects which have been heavily researched by others in recent years. Societies occur among very few vertebrates and the insects, the world's champs in mimicry including behavior mimicry, a possible clue.



4. This book (Gould's last) is a behemoth. With over 1400 pages, it becomes a physically taxing task to read it. This task is not lessened by the verbiage (and verbosity) that exemplify Gould's style. That being said, this book emcompasses such marvelous theoretical views and includes such a thorough history of evolutionary ideas, that it would be a shame to allow its size and density to prevent you from reading it. Gould spent his entire life pondering the big questions of evolutionary thought, and his ponderings are here revealed with significant insight into the roots of the questions themselves. It is an endeavor to read (as it was a lifetime to write), but the rewards of such an endeavor are innumerable and priceless.



5. An excellent academic book that covers Gould's life work in detail. It will (or should) become a standard reference for postgraduate students of biological evolution. It is not easy reading but is helped by an excellent table of contents; it summarises the main arguement of the book. My only critisism is that it seems to neglect the work of Simon and Salthe, both of whom have made significant contributions to a heirarchical (multi-level) theory of evolution.

5 comments about Hidden Order: How Adaptation Builds Complexity (Helix Books).

1. In the worlds of Complexity and Artificial Intelligence, the name of John Holland is revered, and for good reason. One of the most important contributions to both fields was Holland's invention of genetic algorithms, a class of optimization techniques that applies a survival-of-the-fittest heuristic to a broad range of otherwise intractable problems. He is certifiably a genius, and his words on the subject of complexity should be considered close to the gospel.

   To the benefit of all mankind, this god of complexity has seen fit to lay down his word on the subject in a manner suitable to the masses. He posits seven basic properties of complex adaptive systems (worth reading and memorizing in their own right), then uses the rest of the book to demonstrate that adaptive systems possess these properties and shows us how a computer can capture such adaptive mechanisms. Pure gold and totally accessible.

   This book excels as an exposition of complex adaptive systems for the masses, and as a tutorial for the technically inclined. If you are so technically inclined, follow this book with Holland's "Emergence" and "Adaptation in Natural and Artificial Systems." Then head on over to Goldberg's book on genetic algorithms and maybe some Koza (a quick Amazon search can find these for you).




2. The ideas presented in this book by John Holland are no doubt interestring. The thought of spontaneous self-organization though hardly new has intrigued humans for centuries. Intuitively it makes sense and appeals to most peoples physical and methaphysical sensibilities. We know and hope that there is more to life than our common sense knowledge of it and the often dull and mechanistic accounts of natural science. Emergence theory therefore has an immediate appeal. Holland manages to keep this "flame" alive for one chapter (the first one) then the wholle enterprise is drowned in techno babble and most "non-hacker" readers are bored and dissappointed. This book is one more instance of a genuinly interesting idea being mercilessly slaughtered by bad writing. It's a true waste. It makes you wish writing courses were made compulsory for natural scientists and techo folks. Unfortunatelly it is hard to reckommend a better book on this subject... Most of the existing books are either written by litterary incompetent but hard core techno devotees or by soft science writers ruminating the self evident and riding the tidal wave of hype. All for the buck and a snapshot in the spotlight. A non-trivial sign of an over-hyped field of inquiry, dangerously bordering the realms of pseudoscience. At least chaos theory had Edward Lorenz as a respectable and astute front figure, managing to keep the delicate balance between scientific integrity and popular appeal. As for emergence theory that post is still vacant. Holland may be an important contributor to the field of emergence theory but he fails the requirements for that post.



3. I think this is an excellent book for someone interested in constructing complex adaptive systems. It clearly lays out the technical guidelines that you would need. And of course, it was written by the man who originated genetic algorithms!

   However, if you are new to the phenomena of complex adaptive systems (CAS) or agent-based models (ABM), this might not be the best intro book for you. This is particularly true if you are wondering what a genetic algorithm is right now. I think you will get the most out of the book if you are already somewhat familiar with CAS and ABM as Holland does not dwell on illustrative examples. (Yes there are examples, but they are very short compared to other authors on this topic.) Because of this, I think this book will be rather dry and technical and non-intuitive for a real newbie. If you have no idea where to begin, try _Growing Artificial Societies_ by Joshua Epstein and Robert Axtell.

   One final comment: for excellent in-depth look at the reiterated Prisoner's Dilemna model with genetic algorithms that Holland briefly discusses, read _The Complexity of Cooperation_ by Robert Axelrod. (Axelrod and Holland mention each other in their books.)




4. It gave me the basic concepts in very clear and rogorous way



5. Hidden Order is a seminar re-arranged into a book. The outcome is not a good read. It is tedious and lacks interesting cases.
   If complex adaptive systems are of interest, take a class and skip this book.

4 comments about The Essence of Chaos (The Jessie and John Danz Lecture Series).

1. Edward Lorenz takes a complicated topic and makes it accessible for all people, regardless of prior knowledge of chaos theory. He provides interesting and easy to follow examples of chaos, fractals and complexity. The illustrations are helpful and he includes a glossary of terms to aid the beginning chaos enthusiasts to quickly become familiar with the terminology. Mr. Lorenz gives a brief history of chaos and explains how it is used in the study of mathematics, meteorology, economics, music, and other fields. The book is very interesting and is highly recommended for those who would like to acquaint themselves with the exciting world of chaos.



2. Lorenz has done it again. This is a terrific inside look at chaos by the man who made Gleick's book possible. And it had a few interesting new ideas too--who would have thought there was a different way to present fourth-order Runge-Kutta? Who would have thought Runge-Kutta could convert a phase-space circle to a nice-looking fractal attractor? A good book for the air plane.



3. My first intro to chaos was Gleick's book *Chaos: Making a New Science* which focused on the history of the discovery of chaos. Although this was fascinating - and a good read for those just learning about dynamical systems, strange attractors, and the like - Lorenz's *Essence of Chaos* was much more satisfying. Lorenz analyzes specific chaotic functions, gives you the math (equations are in the appendix) and generally accomplishes what the title suggests - that is, exploring the essence of chaos. I highly recommend it for anyone interested in this deeply fascinating subject.



4. Lorenz did a great job when he wrote this book!
   The very first time when I heard of chaos theory was year ago while watching some old documentary about Nostadamus. In film was mentioned chaos theory and said that acceptance of it by many people could change whole look to life and so on. Movie left to me questions - what is that theory, what it's standing for.
   Finaly my interest lead me to this book and it clearly showed me what kind of staff is that chaos theory! That was and is really intriguing!
   Book is well written. There was of course some places that wasn't easy to understand. I myself have studied high math,encountered differential equations but anyway had some difficulties. That's why not 5 stars to book - it's really not for absolutely everyone although almost close to it. I couldn't stop it reading, I was done in two days.
   This book encouraged me for further reading.

5 comments about Six Degrees: The Science of a Connected Age (Open Market Edition).

1. The book is not a user's guide to social networking. This is not "Networking for Dummies"! It is a thoughtful treatment by an academic of a fascinating topic - or to be more precise - an intriguing network of interrelated topics.
   
   In presenting the material in his book, Dr. Watts tells two stories in parallel. At one level, he describes the evolution of his work and that of his colleagues in trying to solve the problem of modeling and understanding the dynamics within a wide variety of types of networks. The networks described include electric power grids, social networks, AIDS and Ebola virus epidemics, hierarchical organizational charts in Fortune 500 firms and financial markets. At another level, Watts uses the story of the arc of his research as a case study to describe the emergence of a whole new branch of science: the science of networks. In one sense, as I made my way through the ten chapters of this book, I felt I had been invited into a microbiology laboratory to view the results of experiments in which Watts and his gifted colleagues has served as human Petri dishes that had hosted the incubation of germs of ideas that had been cultured from a wide variety of disciplines and streams of thought.
   
   As a recruiter and an avid practitioner of social networking, I found much to ponder in these chapters. Chapter 5, "Search in Networks," is particularly relevant to the problem of how best to think about finding the right person via directed searches or broadcast searches. I also found enlightening Watt's tracing of the development of the popular concept of "Six Degrees of Separation" from its inception in 1967 the research of social psychologist Stanley Milgram into the "small-world problem." through its current level of cachet in popular parlance.
   
   As a Renaissance Soul who believes firmly in the value of helping companies to discover and to hire broadly educated leaders, I was particularly encouraged by Chapter 9, "Innovation, Adaptation, and Recovery." Standing on the shoulders of two MIT professors, Chuck Sabel and Michael Piore, whose 1984 book, The Second Industrial Divide, warned of a sea change in industrial organization, Watts surveys the challenges of organizational structure and communication in an age of ambiguity. Implicit throughout this book is a point that he makes explicit in this chapter: the only way to function effectively in this world of growing complexity and ambiguity is to utilize strategies of collaboration across traditional boundaries. This principle is true in facing the challenges of creating a new science of networking. Boundaries had to be crossed and chasms bridged that had traditionally separated scientists in their own fiefdoms of physics, economics, mathematics, sociology in order to be able to begin to model network behaviors and dynamics. I see the same dynamics at work in the nascent field of nanotechnology, in which biologists, physicists, material scientists, electrical engineers, optics specialists and software engineers are all working together to solve problems and grasp emerging opportunities.
   
   In much the same way, the only reasonable approach to resolving complex challenges within organizations is to create collaboration strategies that connect individual and teams that traditional have done their work in isolation from one another. As a compelling case in point, Watts dissects the Toyota-Aisin crisis of 1997 and its stunning resolution.
   
   I am more convinced than ever before that the challenges of complexity and ambiguity in the world of business will be faced most successfully by companies that have the vision to hire as leaders Renaissance Men and Women who understand at the very core of their being the value and power of collaboration across traditional boundaries of thought, academic discipline and functional role within an organization.
   
   I am grateful to Dr. Watts for taking his experience from academic work and making it applicable and accessible to those of use practicing outside the world of academia.



2. I wrote this book review as an assignment for a class. Its intended audience was sociologists unfamiliar with network theory. The intended audience for the book though is much wider. If you want the math, read academic journals.
   
   In the first chapter of Six Degrees Duncan Watts notes that gossip, power outages, epidemics, even properties of the human brain such as consciousness are phenomena that may be understood as emerging from the interaction of their constituent elements. Through such examples, he calls attention to the broad applicability of his subject matter. Having provided this motivation, Watts spends much of first half of the book discussing what he knows best, "small world" networks. In the second half he presents a network perspective for a wide range of topics such as epidemics, externalities, speculation, social decision making, and organizations.
   
   Like many academics marketing books to non-academics, Watts skillfully weaves his personal story with the science. His personal story is not only provided to keep laymen interested. Watts is now a member of the sociology department at Columbia University, but one can't help but wonder whether he identifies as a sociologist? How would other members of the discipline respond to a youngster whose PhD is in theoretical and applied mechanics who may never have read Durkheim? His early collaborators were mathematicians, physicists, and computer scientists lodged in appropriate departments. Watts though, has become a strong proponent of interdisciplinary science, and he respectfully acknowledges research that has been done in anthropology, sociology, psychology and economics.
   
   His first foray in the social sciences was inspired by the "small world" phenomenon. When two people are surprised to learn they have mutual acquaintances, someone often says, "It's a small world." In 1967, social psychologist Stanley Milgram decided to investigate how small the world really is. He tasked randomly selected residents of Boston and Omaha with getting a letter to a stockbroker who lived in Massachusetts. The rule was, they could only send the letter to people they knew on a first name basis. Amazingly, the letters that reached their destination usually did it in just 6 steps. This finding was then misconstrued and became the urban legend that there are six degrees of separation between any two people. Despite the widespread interest in the small world phenomena, little progress was made understanding it over the next thirty years.
   
   Watts got interested in this problem when he was a graduate student in theoretical and applied mechanics. He and his advisor, Steven Strogatz, had been trying to understand how crickets' chirping becomes synchronized without a conductor cricket. Watts surmised that the timing of a cricket's chirp must be influenced by where it is located and the other crickets it is listening to. The ability to synchronize may depend on the structure of this network of crickets. The relationship between network structure and network phenomena such as synchronicity suddenly seemed broadly important, and he was surprised to learn how little mathematical attention it had garnered. Recalling the idea of "six degrees of separation," Watts and Strogatz turned to social networks and set about building simple models. Where Milgram had asked, "How small is the world?" they were now asking, "What does it take to make a world small?" This reframing of the problem was fundamental to the contribution they were to make.
   
   Watts and Strogatz settled on modeling just two facets of social networks. One was the "small world" aspect, quantified as average path length (the number of links required to connect two randomly chosen people). The second was clustering, the extent to which my friends overlap with my friends' friends. What makes small world networks surprising is that short path lengths and high clustering are inherently antagonistic. Paul Erd?s and Alfred R?nyi rigorously proved that path lengths are short in networks with no inclination towards increased clustering, a random graph in the parlance of mathematicians. At the opposite extreme, if everyone was friends with all of their friends' friends, short path lengths would be impossible (in fact social groups would be completely disconnected from each other). After countless computer simulations, Watts had two important results. The alpha model captured the small world balance of path length and clustering. The beta model showed that if a network was systematically clustered, to the point of fragmentation, just adding five random links (edges) halves the average path length. He then began acquiring and examining network data sets. Remarkably, Hollywood actor collaborations, the neurology of C. Elegans, the power grid of the Western United States, interlocking boards of directors and the world wide web are all small world networks.
   
   Next Watts reviews the work by L?zl? Barab?si, a physicist at the University of Notre Dame. His major contribution is research on scale free networks. Sociologists have long been concerned with questions surrounding the number of connections (degree) people have. Barab?si realized the importance of the degree distribution in a network. The degree distribution of many networks is approximately Poisson but Barabasi showed that the degree distribution of other important networks follows the highly skewed power-law. The distribution of wealth and the size of cities both fit this model. Furthermore he showed that this distribution will follow if the future growth rate is linearly related to the present size. This has obvious implications for these two examples and calls to mind Merton's Matthew Effect.
   
   Barab?si's book, Linked, is similar to Six Degrees in that is geared to the general public and reviews many of the most important advances in network scholarship. Do Watts and Barab?si overstate their case? Rather than get bogged down in the semantic debate that is likely to arise from the claim to a "new" science, we should appraise the value of this line of research. It clearly has potential but Watts himself sometimes alludes to the difficulties in achieving that potential. Watts' work is mostly theoretical. Six Degrees offers a thought provoking network perspective on many topics but little help harnessing the theory in empirical work. Appropriate data may be hard to come by. Perhaps Watts has provided ideas that creative empiricists will find ways to exploit, but there are methodological challenges that may prove to be stubborn.
   
   Despite some important exceptions such as Granovetter's Strength of Weak Ties sociologists have tended to take one of two approaches. One was to focus on the relationship between social structure and network structure. The other was to view network ties as sources of information or influence. This means exploring the association between position in a network, and a node's identity or power. Watts is right to call attention to the fact that these approaches usually ignored dynamics: changes in the network structure (changes in network connections), and what individuals do on the network (search for information, spread rumors, make decisions). Network data that captures these dynamics may be harder to come by.
   
   Furthermore, large detailed datasets may be limited by the computational power available. Even simple computer simulations can be very computationally demanding. Threshold models of decision making, discontinuous phase transitions and cascades - many of the fundamental concepts in the study of networks are nonlinear. Proving the existence of causal relationships is always a challenge but these complex systems make a hash of everything. The measured effect of an independent variable, on average or at the margin, tells us little about the importance of that variable.
   
   Despite a reasonable display of humility and respect, Watts should be criticized for the sociology he leaves out. Neither space limitations, nor a rush to publication can justify the gaps in his otherwise helpful recommendations for further reading. For example, Blau, Burt, Coleman, Homans, Laumann, Marwell and Oliver are conspicuously absent from the list. Perhaps this observation should not be overanalyzed but it does brings us back to how Watts will be received by sociologists and what impact he and scholars outside the discipline will have on sociology. It is hard for this reviewer to understand how anyone who reads this book could come away uncertain of the value of mathematics for theory development as well as empirical analysis. Model building can simplify and clarify, enhancing our intuition. Watts would never argue that all sociologists should drop what they're doing and begin running computer simulations, just that we should be open to such approaches. As he points out, "For any complex system, there are many simple models we can invent to understand its behavior. The trick is to pick the right one. And that requires us to think carefully, to know something about the essence of the real thing." Sociologists know something about the real thing. That's why we can't leave all the modeling to physicists and economists.



3. No more other words to say, I am really satisfied with the service!



4. We used this book in a doctoral seminar addressing shifting practices of "meaning making" in a networked society. It was the one book that everyone agreed was outstanding in all areas: aside from the depth and level of scholarship in Watts's work, he also has an extremely approachable style, one that will make the book useful to scholars and laymen alike.



5. Random Graph Theory: Image throwing a box full of buttons on a table and then choosing a pair of buttons at random and connect them with a piece of string. What would the buttons look like over a period of time. "In particular, what features could we prove that all such networks must have?" If you pickup one of the buttons what would be its connected component? "The fraction of the nodes connected in a single component change suddenly when the average number of links per node exceeds one." If we add enough thread so each button has one thread the fraction of the graph that occupied by the largest component suddenly jumps from almost zero to one. A phase transition from unconnected to connected and the point this happens is called the critical point. "Phase transitions of one sort or another occur in many complex systems and have been used to explain phenomena as diver as the onset of magnetization, the explosion of disease epidemics, and the propagation of fads. In the particular case, the phase transition is driven by the addition of a small number of links right near the critical point that have the effect of connecting many very small clusters into a single giant component, which then proceeds to swallow up all the other nodes until everything is connected." "So the presence of a giant component means that whatever happens at one location in the network has the potential to affect any other location." "The line between isolation and connectedness is thus an important threshold for the flow of information, disease, money, innovations, fads, social norms, and pretty much everything else that we care about in the moder society. The global connectivity should arrive not incrementally but in a sudden, dramatic jump tells us something deep and mysterious about the world." Almost everything we know about complex networks tells us that "they are not random." "Nevertheless, if we would like to understand the properties and behavior of real-world networks, the issue of nonrandom structure is one that eventually has to be faced."

5 comments about Sync: How Order Emerges from Chaos in the Universe, Nature, and Daily Life.

1. In his 1987 book Chaos, James Gleick noted that choatic systems produce periodic patches of order.
   
   At that time and during that state of research, the answer to the question of why this should be so remained largely unresolved. And to be honest, after reading this book and learning about the sync or synchronicity of how fireflies light up the night in unison and how inanimate pendulums can come to swing in unison the question will be still be largely unresolved.
   
   However, you will leave this book with some additional interesting food for thought.
   
   Why do periodic patches of order emerge in choatic systems?
   
   Well, one answer suggested seems to be that if that chaotic system produces periodic amounts of a like particle -- like an electron -- that those like particles can generally be relied upon to behave similarly. Then maybe it's the delicate calculus of these mutually constitued similar behaviors that helps give rise to the rise of order.
   
   But maybe not...and such is the state of research into this important issue.



2. This book gave both nature and theoretical explanation of what sync is and how it might
   happen. Of course, its raminifaction still need a lot of exploration. This book is a good start and definite a good read for scientific inquiring mind. Read it and you know if you sync with this book.



3. What a fun book. Strogatz has managed to talk about the leading edge of mathematical modeling without a single equation! He uses a comfortable prose and never strays too far from the story of his research. The reader is treated to a view of the way that the world network of scientists organizes itself within areas of research and finds unions where research from one speciality can contribute to another. Who would have thought that the western power grid, the Internet Movie Database and the nervous system of a worm called C. elegans could be effectively modeled with the same operational principles.



4. What I found most interesting about Strogatz's sync theory was the position that it did not require an extensive measure of complexity in order to achieve synchronization. It merely required a critical mass or critical repetition in order to effectuate a phase transformation. The phenomenon of resonance performs similarly. Synchronization may be a form of resonance which has been overlooked, thus far, in our reality (biosphere).



5. Author Steve Strogatz's book "Sync" ostensibly concerns the spontaneous synchronization of oscillators, where an "oscillator" is anything that exhibits periodic behavior -- be it a clock, a flashing firefly, or an electron in a superconductor.
   
   The book is clearly modeled on James Gleick's book "Chaos": both books follow various researchers who originally work in isolation but who gradually recognize that they are investigating different aspects of the same phenomenon. As Gleick did for chaos, Strogatz tries to portray spontaneous synchronization as a fundamental, unifying phenomenon in nature. However, many of Strogatz's examples are unimpressive: sleep patterns, the coordinated flashing of lightning bugs, etc. In the more important cases -- the heart's pacemaker cells, phase transitions -- the mechanisms' details haven't been elucidated, so it's not clear how synchronization actually operates. Gradually Strogatz wanders: He argues that in order to progress, science should abandon its traditional analytic approach of investigating the bits of a system and instead should investigate the interactions between the bits; in this connection, he discusses the game "6-degrees of separation," in which very different people are "linked" by chains of acquaintances.
   
   (Strogatz also follows Gleick's footnote format, which is a nuisance.)
   
   In reading this book, I had hoped to find deep insights from a principal investigator in the field; instead, I found entertainment for the math-phobic.

5 comments about Emergence: The Connected Lives of Ants, Brains, Cities, and Software.

1. This book is well written and provides an insight to the science of emerergence and how it can help exlain the fundamental texture of everything from ant colonies to cafe-society. It is one of those rare books that readers will benefit from reading many times. For those with a scientific appreciation it fully satisfies while those readers with a more cultural focus will still find it very readable.
   
   The subject matter is highly important and may help create models of better societies in the economically and environmentally challenging years ahead. This book undoubtedly helps us to see a way.



2. This is a pretty good read - it moves quickly and doesn't get you bogged down in the dna of the concept of emergence. go to wikipedia, read it. then pick up a copy of this and it will provide more context and usefulness. while this may not be the 'grand slam' of books...and to some degree it may be viewed as a popular fad topic...this book is better written than many that end up in the waste bend after page 47. if highlighter markings and cryptic notes in the margin are an indicator for me then it is safe to say that i got my money's worth...and...it contributed to my ongoing pondering of this and many other esoteric terms from the science realm.



3. I purchased this book on something of a whim; it was listed as recommended by Amazon and looked like something worth checking out. This is appropriate because software systems that make recommendations based on history and feedback are one of the topics that get discussed in this book. The concept appealed to me for a number of reasons. First, it seemed like a fascinating study of complex systems and the relationship therein between the components, the system as a whole, and that which may be greater then the sum of its parts - that which is emergent. Which in fact, for a while it was. Second, I appreciate the idea that a city is a complex system that is not dissimilar to other complex systems. And third, I felt like taking a chance on something that just sounded interesting. Sadly, after high expectations brought on by a well developed first half, this book ultimately disappoints.
   
   Credit where credit is due, this book starts off as well as a book can. In keeping with the old adage that a picture is worth a thousand words, there is a wonderful illustration at the start of this book featuring a map of Hamburg dated circa 1850 next to a diagram of a human brain. Whether there is ultimately anything to them or not, the similarities are astounding. It really went a long way towards grabbing my attention and making this book one that I looked forward to reading. For half of the book, my expectations were met.
   
   The first three chapters take the seemingly mundane and unrelated topics of ant colonies, computer programs based on slime mold observations, and city layout, and make an effective comparison. Something I really liked early on about this book was its observation that both ant colonies and cities expand with an order that suggests a central plan, when in fact the main force behind their development is the elemental units just doing the things that they do. Soldier and worker ands don't do their jobs because the queen orders them to, they do them because taking care of the queen keeps the colony alive, thus sustaining their existence. Neighborhoods don't spring up because someone issues a decree to build homes, they spring up because people have wants and needs regarding where they live. And their existence in a certain place creates a continuing cycle, almost fractal in nature, of more people with their own set of wants and needs. The concept of evolution is also thrown in, and quite effectively.
   
   I think that the strongest point the book makes is that cities are not just clusters of people, they are patterns in time. Human beings wired the way they are seem predestined to create printing presses, newspapers, radios, communications networks, TV's, and internets. But here lies the problem with this book. This is potentially a great point, and I would argue a correct one. It's just that it comes along right at about the halfway point in the book. And after that there not much else other than words. The first half of this book does what the first half of a book should do, it develops an idea. But the development of an idea needs to lead to some sort of conclusion that contains some sense of resolution. Unfortunately, somewhere shortly after the start of chapter 4, this book lets go of all of the cohesion it so nicely developed and spins into seemingly endless and tired commentary about video games and the web. Moreover, the commentary is not very good, and becomes repetitive. By the last couple of chapters it becomes quite clear the only thing concluded will be that the author thinks that in a few more years something really significant is going to come about from recent technological changes. They always do. That in and of itself is not worth very much. In the author's defense, I did read this book in 2007 and it was written in 2000. But still, a book should say considerably more this one does.
   
   If the second half were as good as the first, this book could have been ground-breaking. I appreciate the first half, so I don't consider it a complete waste. However be prepared for quite a let down - 2 stars.



4. I saw Steven Johnson's lively and a compellingly fascinating presentation on the topic of the book at a conference, which inspired my desire to read his book.
   
   
   Unfortunately, the 250+ pages of the book provide very little insight beyond a 30+ minute presentation. The writing style is not forceful or engaging, but rather dull and lifeless. The lasting feeling is that the author is attempting to make the book accessible to a group of smart 10 year olds by using short sentences, simple vocabulary and endlessly repeating the same ideas over and over again.
   
   The initial excitement wears off after about first 50 pages and the impetus to try to read it would help you stumble through the drudgery of another 50 pages, but except to give up sometime soon afterwards.



5. The property of "emergence" is essentially the top-level or macro-level view of the behavior or intelligence of a system. The system can be an ant colony, the Internet, a nation, or any collection of individual agents or actors.
   
   To take one example, an ant colony, can be studied in terms of the individual intelligence and actions and behavior of the individual ants in the colony. This is the micro-view.
   
   However, collectively, the ants function together in a system (i.e., the colony). Thus, the colony can also be studied in terms of its behavior, intelligence and actions. This is the macro-view. This is the systems view. Emergent properties are the top level properties that "emerge" from the properties, functions, behavior and actions of the individual units in the system (i.e., the individual ants).
   
   Emergence is a very important concept, especially in terms of group behavior, the world wide web and the Internet, as well as in artifical intelligence and biological and ecological systems. Emergence is also a very important concept in "swarm intelligence" and "hive" type intelligence. These are important concepts for computer science, among many other fields.
   
   Thus the importance of this book which elucidates the concept of "emergence" by describing it in the context of several different areas of study in which it appears.

5 comments about Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity).

1. At the time of writing this review, this book isn't searchable through Amazon, that's too bad because if you're reading the reviews wondering if it's worth buying, just browsing through any page from the intro or appendix B would clearly resolve any remnant hesitation. This book is a must have for anyone even remotely interested in complex adaptive systems. Scott Page and John Miller dress the landscape and state of the art of computational social science, the issues are motivated from the ground up and the existing approaches to resolve them explicitly detailed, yet using clear and jargon free language. For example, descriptions of the many concepts repeatedly used in the scientific method (of CAS et al) such as ergodicity or optimization theory are refreshing and insightful, simply stuff you don't get from textbooks, but rather that one would learn over years of experience doing.
   
   In summary, the authors are handing us an expert summary of literature and developments of a complex field in a concise, fun and delightful read, it would be a shame to miss it.



2. Living systems are generally complex, dynamic adaptive systems with emergent properties that analytical models attending only to the local interactions of the system fail to capture. We must complement the standard analytical methods of physics, biology, and economics by additional mathematical tools, such as agent-based simulation and network theory.
   
   A complex system consists of a large population of similar entities (e.g., human individuals) who interact through regularized channels (e.g., networks, markets, social institutions) with significant stochastic elements, without a system of centralized organization and control (i.e., if there is a state, it controls only a fraction of all social interactions, and itself is a complex system). A complex system is adaptive if it evolves through some evolutionary (genetic, cultural, agent-based silicon, or other) process of hereditary reproduction, mutation, and selection.. Characterizing a system as complex adaptive does not explain its operation, and does not solve any problems. However, it suggests that certain modeling tools are likely to be effective that have little use in a non-complex system.
   
   Such novel research tools are needed because a complex adaptive system generally has emergent properties that cannot be analytically derived from its component parts. The stunning success of modern physics and chemistry lies in their ability to avoid or strictly limit emergence. Indeed, the experimental method in natural science is to create highly simplified laboratory conditions, under which modeling becomes analytically tractable. Physics is no more effective than economics or biology in analyzing complex real-world phenomena in situ.. The various branches of engineering (electrical, chemical, mechanical) are effective because they recreate in everyday life artificially controlled, non-complex, non-adaptive, environments that can directly apply the discoveries of physics and chemistry. This option is generally not open to most behavioral scientists, who rarely have the opportunity of ``engineering'' social institutions and cultures.
   
   Miller and Page stress that complex systems cannot be properly modeled using the statistical and mathematical tools associated with differentiable manifolds and normal statistical distributions. Rather, complex phenomena exhibit power law behavior in which statistical distributions have "fat tails" that lead to considerable activity far from the distributions central tendency. A rather stunning example, discussed in Chapter 9, is the size distribution of wars in the world occurring between 1820 and 1943. When the number of deaths in a war (a good measure of the size of the war) is 10 to the power n, the number of wars with this size is about 2 x 3 to the power 7-n.
   
   Miller and Page do a find job of making complexity analysis accessible to the non-expert, without overwhelming the reader with specialized aspects of agent-based modeling or dynamical systems. They provide an exciting stepping-off point for detailed studies in particular disciplines.



3. I found this book to be a bit more technical than I expected. Very good reference book.



4. Sometime I encounter books that are extremely important, that give me an appreciation for a knowledge domain I do not know enough about, and that I simply cannot read and review.
   
   This book, and Generative Social Science: Studies in Agent-Based Computational Modeling (Princeton Studies in Complexity) are two such books. I got half-way through this one, did the introduction to the other, from which I was immediately grabbed by the concept of:
   
   "instead of explaining it, can you grow it?"
   
   Howard Bloom, in Global Brain: The Evolution of Mass Mind from the Big Bang to the 21st Century teaches us that the only way to create a sustainable peace in the Palestine region is to provide absolute security for an entire generation, and raise two whole generations, one on each side, from kindergarten on us, generations that do not consider "the other" to be "pigs and monkeys" by the age of five.
   
   Similarly, the literature on wealth of networks and the fortune at the bottom of the pyramid is growing, and I am convinced that public intelligence (decision support, full disclosure, end of information asymmetries) is going to accomplish two things in the next twenty years:
   
   1) Eradicate corruption and enforce the triple-bottom line
   
   2) Elevate five billion poor by teaching them one cell call at a time so that they can create infinite stabilizing wealth.
   
   See for example:
   Infinite Wealth: A New World of Collaboration and Abundance in the Knowledge Era
   The Wealth of Networks: How Social Production Transforms Markets and Freedom
   Revolutionary Wealth: How it will be created and how it will change our lives
   The Fortune at the Bottom of the Pyramid: Eradicating Poverty Through Profits (Wharton School Publishing Paperbacks)
   
   So the very best thing I can say about this book is that I am glad I bought it, I am very glad to have a sense, however weak, of this important exploratory area, and now I know that I need a team of generative social scientists that can do complex modeling for peace and prosperity solutions.
   
   See also, just published at Amazon and free online at Earth Intelligence Network, Collective Intelligence: Creating a Prosperous World at Peace
   
   I urge one and all to become familiar with World Index of Social and Environmental Responsibility (WISER), as best I can tell that is the center of gravity for empowering individuals with deep knowledge of the true costs and many human rights abuses and other crimes that we support today for lack of knowledge. I also recommend the pioneering EarthGame work of Medard Gabel, at BigPictureSmallWorld.



5. The authors do an excellent job of introducing the field to an educated audience. Any one who has a general college level education can read and understand the basics after reading the book. Tables and charts succinctly illustrate points Miller and Page make and illucidate the text.
   
   If you are looking for a book that discusses progamming, how to do, or other deeper aspects of the field, you will be disappointed. However, if you are just curious and want a good general introduction to the field, perhaps with the goal of further exploration, it is a good anchor from which to base your learning.