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.

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.

Mathematical Models for Society and Biology, 2e, is a useful resource for researchers, graduate students, and post-docs in the applied mathematics and life science fields. Mathematical modeling is one of the major subfields of mathematical biology. A mathematical model may be used to help explain a system, to study the effects of different components, and to make predictions about behavior. Mathematical Models for Society and Biology, 2e, draws on current issues to engagingly relate how to use mathematics to gain insight into problems in biology and contemporary society. For this new edition, author Edward Beltrami uses mathematical models that are simple, transparent, and verifiable. Also new to this edition is an introduction to mathematical notions that every quantitative scientist in the biological and social sciences should know. Additionally, each chapter now includes a detailed discussion on how to formulate a reasonable model to gain insight into the specific question that has been introduced. - Offers 40% more content – 5 new chapters in addition to revisions to existing chapters - Accessible for quick self study as well as a resource for courses in molecular biology, biochemistry, embryology and cell biology, medicine, ecology and evolution, bio-mathematics, and applied math in general - Features expanded appendices with an extensive list of references, solutions to selected exercises in the book, and further discussion of various mathematical methods introduced in the book

Thirty years ago, biologists could get by with a rudimentary grasp of mathematics and modeling. Not so today. In seeking to answer fundamental questions about how biological systems function and change over time, the modern biologist is as likely to rely on sophisticated mathematical and computer-based models as traditional fieldwork. In this book, Sarah Otto and Troy Day provide biology students with the tools necessary to both interpret models and to build their own. The book starts at an elementary level of mathematical modeling, assuming that the reader has had high school mathematics and first-year calculus. Otto and Day then gradually build in depth and complexity, from classic models in ecology and evolution to more intricate class-structured and probabilistic models. The authors provide primers with instructive exercises to introduce readers to the more advanced subjects of linear algebra and probability theory. Through examples, they describe how models have been used to understand such topics as the spread of HIV, chaos, the age structure of a country, speciation, and extinction. Ecologists and evolutionary biologists today need enough mathematical training to be able to assess the power and limits of biological models and to develop theories and models themselves. This innovative book will be an indispensable guide to the world of mathematical models for the next generation of biologists. A how-to guide for developing new mathematical models in biology Provides step-by-step recipes for constructing and analyzing models Interesting biological applications Explores classical models in ecology and evolution Questions at the end of every chapter Primers cover important mathematical topics Exercises with answers Appendixes summarize useful rules Labs and advanced material available

The central topic of this book is the mathematical analysis of social systems, understood in the following rather classical way: social systems consist of social actors who interact according to specific rules of interactions; the dynamics of social systems is then the consequences of these interactions, viz., the self-organization of social systems. According to particular demands of their environment, social systems are able to behave in an adaptive manner, that is they can change their rules of interaction by certain meta rules and thus generate a meta dynamics. It is possible to model and analyse mathematically both dynamics and meta dynamics, using cellular automata and genetic algorithms. These tools allow social systems theory to be carried through as precisely as the theories of natural systems, a feat that has not previously been possible. Readership: Researchers and graduate students in the fields of theoretical sociology and social and general systems theory and other interested scientists. No specialised knowledge of mathematics and/or computer science is required.

This edited volume presents examples of social science research projects that employ new methods of quantitative analysis and mathematical modeling of social processes. This book presents the fascinating areas of empirical and theoretical investigations that use formal mathematics in a way that is accessible for individuals lacking extensive expertise but still desiring to expand their scope of research methodology and add to their data analysis toolbox. Mathematical Modeling of Social Relationships professes how mathematical modeling can help us understand the fundamental, compelling, and yet sometimes complicated concepts that arise in the social sciences. This volume will appeal to upper-level students and researchers in a broad area of fields within the social sciences, as well as the disciplines of social psychology, complex systems, and applied mathematics.

The author of the world wide best-seller, Small Is Beautiful, now tackles the subject of Man, the World, and the Meaning of Living. Schumacher writes about man's relation to the world. man has obligations -- to other men, to the earth, to progress and technology, but most importantly himself. If man can fulfill these obligations, then and only then can he enjoy a real relationship with the world, then and only then can he know the meaning of living. Schumacher says we need maps: a "map of knowledge" and a "map of living." The concern of the mapmaker--in this instance, Schumacher--is to find for everything it's proper place. Things out of place tend to get lost; they become invisible and there proper places end to be filled by other things that ought not be there at all and therefore serve to mislead. A Guide for the Perplexed teaches us to be our own map makers. This constantly surprising, always stimulating book will be welcomed by a large audience, including the many new fans who believe strongly in what Schumacher has to say.

Writing about sociocultural evolution is always a complicated enterprise, because the subject is not only difficult in a scientific way but also in a political one. In particular since the events of September 11, 2001 the debates about the differences between cultures and their evolutionary developments have left the fields of pure scientific research once and for all. However, there have probably never been scientific discourses that did not touch the realms of political discussions - Darwin, Marx, the atomic physicists and the recent debates about genetic engineering are just a few examples. The aim of this book is not to take part in these debates but it is written as a contribution to the foundations of evolutionary theories in the social sciences. The readers will have to judge if I have succeeded with it. Perhaps essays like this one will help to clarify the problems we all have to face just now in regard to intercultural discourses. Theoretically and mathematically grounded insights into cultural development as the source of many political problems will not solve to how to deal with them them immediately but may serve as signposts in the long run.

Biologists have long been intrigued and confounded by the complex issues in the evolution and ecology of the social behaviour of insects. The self-sacrifice of sterile workers in ant colonies has been particularly difficult for evolutionary biologists to explain. This text presents an overview of the current state of scientific knowledge about social evolution in ants and shows how studies on ants have contributed to an understanding of many fundamental topics in behavioural ecology and evolutionary biology.

When I started with this book several years ago I originally intended to write an introduction to mathematical systems theory for social scientists. Yet the more I thought about systems theory on the one side and theoretical sociology on the other the more I became convinced that the classical mathematical tools are not very well suited for the problems of sociology. Then I became acquainted with the researches on complex systems by the Santa Fe Institute and in particular with cellular automata, Boolean networks and genetic algorithms. These mathematically very simple but extremely efficient tools are, in my opinion, very well appropriate for modeling social dynamics. Therefore I tried to reformulate several classical problems of theoretical sociology in terms of these formal systems and outline new possibilities for a mathematical sociology which is able to join immediately on the great traditions of theoretical sociology. The result is this book; whether I succeeded with it is of course up to the readers. As the readers will perceive, the book could not have been written by me alone but only by the joint labors of the computer group at the Interdisciplinary Center of Research in Higher Education at the University of Essen. The members of the group, Christina Stoica, Jom Schmidt and Ralph Kier, are named in several subchapters as co-authors. Yet even more important than their contributions to this book were the permanent discussions with them and their patience with my new and very speculative ideas. Many thanks.