Mathematical Models of Social Evolution: A Guide for the Perplexed by Richard McElreath (PDF)

Description

Over the last several decades, mathematical models have become central to the study of social evolution, both in biology and the social sciences. But students in these disciplines often seriously lack the tools to understand them. A primer on behavioral modeling that includes both mathematics and evolutionary theory, Mathematical Models of Social Evolution aims to make the student and professional researcher in biology and the social sciences fully conversant in the language of the field.Teaching biological concepts from which models can be developed, Richard McElreath and Robert Boyd introduce readers to many of the typical mathematical tools that are used to analyze evolutionary models and end each chapter with a set of problems that draw upon these techniques. Mathematical Models of Social Evolution equips behaviorists and evolutionary biologists with the mathematical knowledge to truly understand the models on which their research depends. Ultimately, McElreath and Boyd’s goal is to impart the fundamental concepts that underlie modern biological understandings of the evolution of behavior so that readers will be able to more fully appreciate journal articles and scientific literature, and start building models of their own.

User’s Reviews

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐The book is an interesting approach for applying the mathematics to the biology.The mathematical level don’t be very difficult, but the approach is global in the sense we can read the more important questions of the evolution theory, from the hawk-dove model to the selection within and between groups.It is considered also the signal theory and its cost, correlated to the learning.The mutation is defined as mistake of the evolution.

⭐A truly terrific book — fascinating to read, intuitive, and incredibly well-written. The entire book is terrific, but the sections on altruism, reciprocity, and Hamilton’s Rule are in my opinion the absolute best material on these subjects out there. Highly recommended.

⭐I revel in these equations at work nearly every day as I watch altruism and greed and fear and dating all around me.

⭐I’d normally ding a book like this for having too much dense mathematics. However since the book says it’s a maths book in the title I can hardly do that – the reader has been warned. The problem is that academics like complicated mathematics too much – it’s their way of showing the rest of the world how smart they are.This book is fairly fat. It covers ESSs, kin selection, reciprocity, group selection, signalling, sex allocation, and sexual selection. It starts out by arguing for the value of mathematical models over computer simulations. As an enthusiast for computer simulations I wasn’t entirely convinced by their points. They played down the value of computer simulations, from my perspective. Anyway, eventually they granted their value, but said that they didn’t have space for teaching programming as well – which is fair enough. The rest of the book is mathematical with no simulations or computers involved.Since the book says it’s about social evolution in its title – and one of the authors is interested in cultural evolution – I was expecting some content about gene-meme coevolution. They have a section of “non-genetic replication” and another section on “social learning”. However the coverage of the topic seemed pretty sparse to me. The book mostly consists of basic models of biological interactions.I looked for mistakes while reading the book. I hardly found any. The section on the contentious topic of group selection turned out to be fairly reasonable. It explicitly recognized the equivalence with kin selection – saying that it was just a different accounting method. It also said that it was probably better to use kin selection most of the time. This earns good marks from me. However the history of the confusion associated with group selection received relatively little coverage.One slight problem was that the chapter on “social learning” says that “many smart people have argued that the value of social learning is that it saves us the costs of individual experiments and mistakes”. It then argues against this position. However the argument is basically a kind of mathematical sophistry. It doesn’t follow that the “many smart people” are wrong. They are right, and the authors shouldn’t be picking a fight with them on the flimsy grounds that pure social learners and pure individual learners have the same fitness in a population at equilibrium which contains both types.The book is probably too zoomed in for most students – containing too many details about too few topics. I can easily think of large areas that received little coverage.I learned a bunch of things from the authors while reading the book. I’d read it again. It was a bit heavy going in places, though. The book must have taken much time and effort to write. Respect to the authors for sharing their learning. This book is a welcome contribution to the topic.

⭐It’s a fine book that contains the information. It’s just not as user friendly and accessible as the “Guide for the Perplexed” would seem to suggest.This is a fine book for the mathematics of social evolution. But there’s probably a better book out there — or – if not — there is an opportunity for someone to write one.

⭐This concise book will allow any mathematically competent but sociobiologically inexperienced reader to dive right into the debates about human evolution. Although the many of the models described in McElreath and Boyd’s Guide for the Perplexed come from evolutionary biology and were conceived as genetic models, a great deal of them apply without alteration to related processes in the social world. Take the prisoners dilemma, the battle of the sexes, the Price Equation, or the Phillip Sidney game, honest signaling, and social learning. Everything inside has direct bearing on how we should understand the evolution of social systems, it’s just that the *math* has already been worked out by others in the biological sciences.The social sciences have much to gain from game theory, and this book is a concise, complete and speedy primer.

⭐The mismatch between title and content is perplexing enough: the book is a summary of biological and game-theoretical modeling that has been done and more competently described by others decades ago. These models have little, if any, connection to what one would consider as “social evolution.” The words “society” or “social” do not even appear in the index. The index term closest to the equally absent “culture” is “covariance genetics.” Welcome to social evolution!Even more perplexing: why should a reader perplexed by society be guided away from society and into genetics by, of all people, two anthropologists?

⭐For a mathematically-challenged individual and a novice to cultural evolution, the models explained were tough but the explanations of each were invaluable in providing an understanding of the social world, particularly conflict and cooperation. Strongly recommended to those interested in learning more about social and cultural evolution.

⭐Never learned so much in so little time. It is very well written and easy to understand. Would highly recommend to anyone interested in this area of science.

⭐Dieses Buch ist eine sehr informelle Einführung in Spieltheorie und insbesondere evolutionär stabile Strategien. Wer bereits formales Vorwissen in Spieltheorie hat stört sich evtl. an fehlenden Definitionen und Theoremen.

⭐Not found.

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