Customer Reviews

Evolutionary Dynamics: Exploring the Equations of Life

5 star:		(9)
4 star:		(1)
3 star:		(1)
2 star:		(1)
1 star:		(0)

 

 

This is a remarkable book, absolutely original, containing a lot of material which has never before appeared in book form. It is written in a very accessible style, and leads almost effortlessly from first principles to state-of-the-art research.

The book takes an eagle's view on evolution, covering an vast range of topics from molecules to man. It emphasises analytical methods and presents a large canvas of superbly elegant mathematical models.

The author has chosen a very personal, highly idiosyncratic sample of subjects of amazing diversity, basically because he feels excited about them: and this excitement shows through, and makes the book very engaging, a positively bracing experience. On all of the topics, the author has contributed substantially, and the feel to get it `straight from the horse's mouth' is one of the great assets of the book. I believe that it will be a splendid hit with students, and regret that I did not have anything like that when I was young.

The style of the book is lucid and vigorous, with short, clear sentences, occasionally in staccato style. The mathematics is reduced to the bare minimum. It is incredible how much mileage the author can get out of it. The illustrations play an important role, and are well devised.

The chapters are short, and they address an amazing array of topics, ranging from molecular evolution to evolutionary games, from HIV to cancer, and from cooperation to language. In spite of their different subjects, they are homogenous: first comes a breezy introduction to the biological (or chemical, or linguistic) facts, then a simple model, then an analysis, without heavy machinery, usually leading up to some remarkable results which could not be obtained without mathematics, then a summary in a few short statements and finally an extensive list of references, including both the classics and the very newest results in the field. The fact that in each case, a few pages suffice to start from scratch and lead to the cutting edge of present-day research is quite remarkable.

The book will certainly have a big impact, and raise a lot of follow-up work. There is hardly a better recipe for young PhDs than to pick one of the chapters and start doing their own research. But in addition, `the whole is more than the sum of its parts'. I usually hate this slogan but here it holds in a spectacular way. By simply putting together the different applications of simple models in so spectacularly diverse fields, Nowak's book promotes a radical `hands-on'-approach to evolution which, I am sure, will have seminal repercussions.

This is, quite simply, a dazzling book. Nowak manages to take very deep mathematical ideas that are on the cutting edge of science and make them fun and pretty rigorous at the same time. The review in Nature said "It should be on the shelf of anyone who has, or thinks they might have, an interest in theoretical biology" and I completely agree. The section on HIV, explaining mathematically why there is a long delay between infection and the disease, and how this proposal in 1990 correctly predicted several biolgical facts which were subseqently discovered (but not mentioning execpt in the notes, that this was his work) is truly exceptional. We are moving beyond the "Just So stories" phase of evolution (such as wooly rhetoric about "Selfish Genes") to real, mathematically rigorous, science.

Excellent book for the mathematically and evolutionarily minded. However, not for general reading unless you are doing graduate work in either mathematics or evolutionary biology. Just excellent survey.

There are so many good things to say about this book I think I will begin with my misgivings!

Not a fault of the book, but before reading this you may want to brush up on your math, especially on systems of differential equations and matrix algebra. Martin Nowak is a fluent and elegant writer and this extends to his math, which (for me anyway) flows wonderfully. But I don't spend enough time on math so I had to slow myself down as I read, think carefully and test my understanding.

There is very little 'biology' in this book. It is mostly on the theoretical structures that underlie evolution. I prefer my evolution with rather more biology. I hope someone will write another book (preferably many books) that goes deeper into applying these ideas to living systems (yes, the chapter on HIV was compelling and the chapter on cancer interesting).

I was disappointed by the Further Reading section. It did not provide enough context about the books mentioned or thread them together into a story. In fact, it seemed a bit rushed - and I had set aside some time to read it carefully.

On to the books strengths.

This is one of the best examples of expository prose I have read in a long time. Martin Nowak can make complex ideas clear and not waste a lot of words doing so. Anyone writing about complex topics where it is important to link the math and ideas could benefit from studying this book. As an example, the description of the Chomsky hierarchies of formal languages is the best I have read.

The presentation of the key equations is exemplary. The components of the equation are all labeled and explained. All books that need to explain equations should take this approach. I plan to copy the quasispecies equation explanation and put it up above my desk.

In general, the quality of the graphics is excellent and they really add to the presentation of the ideas. This is not a book for the Kindle or iPad. Get the physical thing (I plan to buy a couple of extra copies for friends and colleagues).

And the content. Evolutionary Dynamics leads the reader through the past two decades work on uncovering the mathematical framework for evolutionary processes. It provides a compelling (I will use this word too often in this review) introduction to evolution and how to formalize it. A good treatment on fitness landscapes (though this is one of the weaker sections of the book - only in cpmparison with the rest of the book though, as it is still excellent).Good coverage of standard topics like evolutionary games, with a very orderly presentation in which understanding is built up from games in infinite populations to games in finite populations with a great treatment of the classic prisoner's dilemma game and an explanation of why each strategy works. I had not thought through the impact of errors on the popular Tit for Tat or Forgiving Tit for Tat. The implications of this are far reaching. Then there are the chapters on evolutionary graph theory and spatial games. Wow. These alone will open wide fields for future research. Absolutely necessary reading. The book concludes with good applications of evolutionary dynamics to HIV, virulence and parasites and cancer. The final chapter on languages evolution is powerful and the insight into coherence threshold and how it determines the maximum size of a search space (with the universal grammar as the search space for language learning) can be applied in many other fields.

Speaking of other fields, I believe that the approach taken in this book to evolutionary dynamics will eventually replace much of what is now called economics. Economic activity is not about finding equilibriums in the allocation of scarce resources. It is about the competition of replicators in dynamic fitness space. Organizations are a form of replicator. In fact may products are also replicators and trends towards modular and configurable systems, collaborative design, just in time production, local production, etc. will make them more so. This book provides some of the formal tools needed to think about these questions. As an example, the model of value provided by Tom Nagle see The Strategy and Tactics of Pricing (5th Edition)when combined with cost to serve provides a definition of advantage which can be interpreted as fitness. The system of features-benefits-value drivers with the value driver equations and data can be modeled using the concepts from von Neuman of reproduction and replication (see von Neuman's The Theory of Self-Reproducing Automata - why isn't this book in print and in wide circulation?). There are other obvious applications. I would love to see a blend (mashup if you prefer) of evolutionary dynamics and parametric design (see Elements of Parametric Design, or even music composed using some of these equations ...

I will reread this book soon and expect to reference it many times. And I hope a soft cover edition at a lower price comes out so that I can give it to many people.

The author picks a variety of sunjects related to evolution (HIV, cancer, language....), and mathematically shows, why it has to be that way!
The mathematics involved is simple (I am an engineer, and I had absolutely no problems understanding the math), yet rigorous enough.

In my opinion, mathematics is not necessary to understand the principles of Darwin's Great Theory (unlike Quantum Theory and Relativity Theory, where without math, you are lost), it greatly helps to make it unassailable.

I recommend this book to anybody interested in the Theory of Evolution, who is not totally afraid of mathematics.

I don't do math, so I must disclose right away that the math was lost on me, except in the context of this equisitely presented book, I am compelled to recognize that mathematics as well as computation science is going to be a major player is the EarthGame, in modeling alternative outcomes for social and cultural complexity, and in cross-fertilizing disciplines by creating a common language.

I tend to be hard on publishers, so in this instance I want to say right away that the Belknap Press of Harvard University has done an absolutely phenomenal job with this book. The paper, the use of color and white space, every aspect of this book is exquisitly presented, and at an affordable price. I therefore recommend this book for content as well as for its artistic context, for both those who love mathematics, and those who do not, but want to understand the promise of mathematics for the future of life.

The text across the book is elegant, clear, easy to understand, and coherent. The summaries at the end of each chapter are in English, and for me at least, obviate the fact that I am mathematically-challenged.

I have a number of notes that merit sharing as encouragement to buy and read this book, one of just two that I found in the right context and price range as I venture into the intersection of modeling social complexity and doing real-time science in the context of an EarthGame where everyone plays themselves. The other book I bought and will read shortly is Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity). Too many otherwise worthwhile books are grotesquely over-priced, and the authors should release free PDFs online in protest and to have effect on this exciting emergent inter-disciplinary endeavor.

The author stresses early on that Information is what evolves--errors are mutations, mutation plus selection in a noisy (i.e. natural) environment is evolution. I like that idea, and point the reader to Hans Swegen's "The Global Mind: The Ultimate Information Process" (Minerva UK, 1995)which first made the connection for be from DNA to World Brain.

The author inspires with his view that the field of evolutionary dynamics is "on brink of unprecedented theoretical expansion." I must say, as one who is focused on connecting all people to all information in all languages all the time, I have been slow to understand that while that is a wonderful baseline, only models can project alternative scenarios into the future, and hence, the modeling of the past is but a prelude to the shaping of the future by displaying compelling alternative paths.

The author sees mathematics as a common language that can help disciplines interact, and when they do so, progress occurs. He speaks specifically of disciplinary "cultures" that must understand each other.

Early on he delimits the book, and in the process notes that mathematical biology includes:

+ Theoretical ecology
+ Poulation genetics
+ Epidemiology
+ Theoretical immunology
+ Protein folding
+ Generic regulatory networks
+ Neural networks
+ Genomic analysis
+ Pattern formulation

The main ingredients of evolutionary dynamics are

+ Reproduction
+ Mutation
+ Selection
+ Random Drift
+ Spatial Movement

Terms of interest (all explained in English not just mathematics):

+ Sequential space
+ Fitness landscape
+ Error threshold
+ Neutral versus random drift

Thoughts that grabbed me across the book (all from the author):

+ Evolutionary game theory is the most comprehensive way to look at the world.

+ Natural selection favors the defectors over the cooperators BUT if there are repeated interactions, cooperation is not assured, but is made possible.

+ Models show alternative scenarios--inclulding coexistence of all.

+ Evolutionary graph theory yields a remarkably simple rule for the evolution of cooperation.

+ Under natural selection the average fitness of the population continuously declines [we're there!]

+ Direct reciprocity is a mechanism for the evolution of cooperation (the collective intelligence world has been calling for reciprocal altruism and a shift to a gift economy with open money and an end to scarcity--I see all this converging).

+ War and peace strategies CAN be modeled (as my own books suggest, the problem is the information asymmetry that Charles Perrow speaks of. Elites make decisions that have consequences for all of us, but they lie to us (935 lies leading to the war on Iraq) and they also externalize costs into the future.)

+ A SINGLE INDIVIDUAL can move an entire population from war to peace.

+ 10 cooperators in a string comprise a sustainable "walker," and is two such cooperative walkers meet, they can induce a "big bang" in which cooperatives sweep the game away from defectors.

+ Cooperators and defectors can co-exist for near-eternity.

+ Evolutionary graph theory can plot relationships (I think to myself, not only of people to people, but costs to things, time, and space).

+ Language makes infinite use of finite media--bulk of progress in last six hundred million years has been cultural, using language, not genetic.

+ The author credits Noam Chomsky with the Chomsky hierarchy relating language to mathematics. I read most of what Chomsky publishes, and had no idea he had done original work in mathematics back in the day.

+ Learning differs from memorization in that the learner is enabled to acquire generalizations that can then be applied in novel circumstances. I strongly believe that we must radically redirect education toward team learning, project learning, learning to learn, and learning in vivo, one reason I want to map every person, every dollar, every thing, every language, every idea, in Fairfax County.

+ Mathematical analysis of language must combine three fields (at least):
- Formal language theory
- Learning theory
- Evolutionary theory

The author concludes that mathematics is a way to think clearly. I cannot disagree, but as I put the book down, VERY PLEASED with the complete package of such very high quality, I was not convinced that mathematics can do intangible value and cultural nuance is multi-cultural context under stress and with time limitations.

The author provides both a bibliographic essay and a superb extensive bibliography, but if I could change one thing and one thing only in this book, it is that I would integrate the two. I have neither the time nor the inclination to look up each cryptic (Bloom, 1997) in the longer list. I would have preferred to see the actual bibliography organized by chapter, with all books on, for example, "Evolution of Virulence" listed there after the explicatory section. This is a nit.

I learned enough from this book to budget for and demand the full inclusion of evolutionary dynamics in all that the Earth Intelligence Network will strive to accomplish in the next twenty years.

Kudos again to the publisher. Nothing gives me more pleasure, apart from intelligent content, than very high-quality materials, thoughtful editing and lay-out, and honorable pricing. This book is a gem in all respects. BRAVO.

I did not appreciate Stephen Wolfam's A New Kind of Science but treasure the book (another enormous gift to mankind at an affordable price) and urge the mathematically-gifted to take a close look at that work.

Other books that have caught my attention as I circle this area of interest:
Panarchy: Understanding Transformations in Human and Natural Systems
Resilience Thinking: Sustaining Ecosystems and People in a Changing World
The Philosophy of Sustainable Design
Green Chemistry and the Ten Commandments of Sustainability, 2nd ed
The Future of Life
Plan B 3.0: Mobilizing to Save Civilization, Third Edition
High Noon 20 Global Problems, 20 Years to Solve Them

I would also point the reader toward Pierre Levy's Information Economy Meta Language (IEML) as one approach to creating a universal dictionary of concepts, easily found on the Internet, and also Doug Englebart's Open Hypertextdocument System (OHS), easily found at the Bootstrap Institute.

I'm a computer programmer with an intererst in evolutionary programming, and I've written my share of implementations. Each turned out to sport unsightly warts with hair. Nowak's book, however, is immaculate. No hair is to be found in this book, no warts. No cruft either.

Nowak's presentations are paragons of lucidity. The illustrations are minor triumphs of graphical communication. And the whole book is tied together around his rigorous model. Nowak writes better than anyone else I have read on such subjects. If there is justice in textbook heaven, Nowak has written an immortal-to-be. Don't miss it

I am neither a biologist nor a mathematician but I found this book very approachable and tremendously interesting. I would enthusiastically recommend it to anyone with a passing interest in evolution who has a basic understanding of ordinary differential equations and linear algebra and who would like to see the nuts and bolts of how evolution works.

This is a wonderful book by a master of the field. Prof. Nowak, who teaches at Harvard, has managed a minor miracle: writing a book on mathematical biology that is mathematically rigorous and extremely readable at the same time.

The book is divided into two broad sections. The first nine chapters explore various abstract models of evolution. Simple models of evolution do not demonstrate cooperation between individuals, while examples of it abound in the real world. This fact quite rightly fascinates the author and informs his presentation. The last four chapters of the book use some of the modeling techniques developed in previous chapters to study real-world systems, such as HIV infection and cancer.

This book is highly recommended for anyone interested in the mathematical aspects of biology. More broadly, it will be of interest to anyone who's interested in mathematical models of complex systems.

In a way this book is one of the very best books in the history of the world, in a way that disappoints however.

I like the author. I like the topic. I buy into the overall thesis (that models of evolving systems will largely replace nearly all of our prior mathematic models). However, this book and the type of modeling it promotes, promotes understanding of modeling systems much much much more than it promotes understanding of nature, real natural selection in extant biological systems, and the space of artificial natural selection systems that computation systems (a la Wolfram's computational equivalent one dimensional cellular automata systems) present.

To pick some fun topics, some fun things in the world that evolve and model them using 8 different kinds of simple math, is fun---but is it serious? Yes an AIDS attribute was correctly predicted by a model in 1990. We get some predictions. But do we lose anything from happenstance bits modeled variously? I think we lose tremendously and the fate of economics, recently, should be to Prof. Nowak, a warning--I hope he takes it to heart.

I feel the book and its milieu is dangerous---to development of knowledge, in EXACTLY that same way economics was never knowledge of economies merely merely merely knowledge of certain fun models made fun by simplifying all the reality interesting stuffs, recalcitrant to our equation formalisms, out, leaving bland rather obvious results. This book is a tour de force of expression clarity--give Prof. Nowak credit for KNOWING his modeling completely enough to be able to completely exposit it clearly wiithout fuzziness. This man knows modeling but but but but (just a mutation for fun fourth) that is not knowing nature, reality, and biologic natural selection.

The genius of the man and the book is really specific and quite pure and limited---turning some evolutionary questions and situation into models of a clear distinct well exposited type. However it is that earliest step---the question FINDING step in being creative---where this author and book pull their punches quite dangerously. I remember Paul Samuelson in Econ 14,01 my freshman year at MIT---in the first 3 weeks he sped through a host of quite obvious simple assumptions that were hugely WRONG, hugely DISHONEST intellectually, and HUGELY costly--a cover story for Harvard MBA greeds was all they amounted to, proved by 2008 and 2009. This author and book are the intellectual equivalent of that mystifying first set of axiom errors that made econ a cover story decades later--this author and book are the professional and impressive beginnings of such a cover story fate for evolutionary modeling of systems.

To fix this whole project and book, MUCH more attention (a nother mutation for fun) has to be paid up front, to the earliest step in each chapter, the first half of each first sentence---we have to direct attention (and modeling effort) at the profound questions, not the easy and silly and shallow questions as is done in this book throughout.

Many of the models presented, and this is a neurotic point to make, are better done with true topology models as Ken Arrow and others did with the concluding steps of General Equilibrium Theory in economics---I would like to read a Topology-filled modeling book by this author someday soon. I also would like to see Nowak married to Michod for five years without divorce to see what they mutually could force each other's brains into. Their combination would produce stupendous greatness of not mere models but of understanding and models directed at profoundest parts of natural selection (well laid out in Michod's latest stuff).

I believe in terms of clear exposition (of a quite limited treatment of its topics) this book is hard to beat, perhaps only Wolfrom's treatment in A New Kind of Science is better. However, Wolfram aimed at better deeper more difficult to fathom but more rewarding to fathom questions. This book skims the surface---impressive but not all that useful.

I believe, truly, half of my current friends, could get any set of top 30 percentile high school students in the world to build equivalent models of the same evolving systems this book builds models of, with just a bit of coaching. Modeling is fun, impresses people naively ignorant of mathematics, but in the end it is easy and a trick of hiding one's assumptions well, a kind of assumption magic trick, misdirect by the variable assignment statements from the simplifying assumptions being inserted.

Harvard loves modeling that is how they (HARVARD MBAs) ruined the world's economy (we have yet to pay for their wealth) the last 3 years. I hate to see that sickness in Harvard culture and personal character being repeated in biology realms. Nowak is nowhere near the subness of MBA subculture so I am not talking about him here at all, rather, I fear his modeling is beginning to do to natural selection what economics did to economies--become a cover story for evil master's degree grads.