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.

This is a masterly theoretical treatment of one of the central problems in evolutionary biology, the evolution of social cooperation and conflict. Steven Frank tackles the problem with a highly original combination of approaches: game theory, classical models of natural selection, quantitative genetics, and kin selection. He unites these with the best of economic thought: a clear theory of model formation and comparative statics, the development of simple methods for analyzing complex problems, and notions of information and rationality. Using this unique, multidisciplinary approach, Frank makes major advances in understanding the foundations of social evolution. Frank begins by developing the three measures of value used in biology--marginal value, reproductive value, and kin selection. He then combines these measures into a coherent framework, providing the first unified analysis of social evolution in its full ecological and demographic context. Frank also extends the theory of kin selection by showing that relatedness has two distinct meanings. The first is a measure of information about social partners, with close affinity to theories of correlated equilibrium and Bayesian rationality in economic game theory. The second is a measure of the fidelity by which characters are transmitted to future generations--an extended notion of heritability. Throughout, Frank illustrates his methods with many examples, including a complete reformulation of the theory of sex allocation. The book also provides a unique "how-to" guide for constructing models of social behavior. It is essential reading for evolutionary biologists and for economists, mathematicians, and others interested in natural selection.

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.

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

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.