- Hardcover: 384 pages
- Publisher: Belknap Press; First Printing edition (September 29, 2006)
- Language: English
- ISBN-10: 0674023382
- ISBN-13: 978-0674023383
- Product Dimensions: 9.4 x 6.6 x 1.3 inches
- Shipping Weight: 2.4 pounds (View shipping rates and policies)
- Average Customer Review: 15 customer reviews
- Amazon Best Sellers Rank: #445,204 in Books (See Top 100 in Books)
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Evolutionary Dynamics: Exploring the Equations of Life First Printing Edition
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I read this book with huge enjoyment. It is wonderfully well presented, and offers a wide range of new insights into interesting and important and emerging topics in mathematical biology. The book will have a wide and enthusiastic readership. (Robert M. May, Professor of Zoology, Oxford University)
This is a brilliant book by the master of his field. Simple, clear and profound on topics of major importance: cooperation, cancer, language, and HIV itself. You can only benefit by learning what Martin Nowak knows. (Robert Trivers, Professor of Anthropology and Biological Sciences, Rutgers University, and co-author of Genes in Conflict)
Martin Nowak has injected rigor and new ideas into the study of the evolution of language and cooperation. This book is brimming with insights and surprising findings and should be of interest to anyone who is curious about these topics. (Steven Pinker, Johnstone Professor of Psychology, Harvard University, and author of The Language Instinct, Words and Rules: The Ingredients of Language, and How the Mind Works)
Martin Nowak is undeniably a great artist, working in the medium of mathematical biology… Nowak has seemingly effortlessly produced a stream of remarkable theoretical explorations into areas as diverse as the evolution of language, cooperation, cancer and the progression from HIV infection to AIDS. Evolutionary Dynamics, based on a course he gives at Harvard, is a comprehensive summary of this work… This is a unique book. It should be on the shelf of anyone who has, or thinks they might have, an interest in theoretical biology. (Sean Nee Nature 2006-11-01)
The lucid presentation, drawing frequently on the author's own research, provides a uniquely compelling introduction to mathematical biology. Nowak aims to demonstrate the power of simple mathematics to illuminate diverse aspects of evolutionary analysis… Evolutionary Dynamics provides a new generation with an opportunity to draw from the masters. (Steven A. Frank Science 2006-12-22)
The book will be a valuable resource both for those familiar with evolutionary dynamics and for those who are interested in learning the subject. (Ross Cressman Mathematical Reviews 2007-01-01)
Two of the crucial processes that drive evolution, mutation and selection, can be described with mathematical equations. This book introduces the reader to the basic mathematical laws that govern the evolution of life… This is a fascinating treatment of evolutionary theory, with many fresh insights. (S.E. Southeastern Naturalist 2007-12-01)
About the Author
Martin A. Nowak is Director of the Program for Evolutionary Dynamics and Professor of Mathematics and Biology at Harvard University.
Top customer reviews
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 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
+ Theoretical immunology
+ Protein folding
+ Generic regulatory networks
+ Neural networks
+ Genomic analysis
+ Pattern formulation
The main ingredients of evolutionary dynamics are
+ 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.
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.
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