Evolutionary Games and Population Dynamics

Every form of behavior is shaped by trial and error. Such stepwise adaptation can occur through individual learning or through natural selection, the basis of evolution. Since the work of Maynard Smith and others, it has been realized how game theory can model this process. Evolutionary game theory replaces the static solutions of classical game theory by a dynamical approach centered not on the concept of rational players but on the population dynamics of behavioral programs. In this book the authors investigate the nonlinear dynamics of the self-regulation of social and economic behavior, and of the closely related interactions among species in ecological communities. Replicator equations describe how successful strategies spread and thereby create new conditions that can alter the basis of their success, i.e., to enable us to understand the strategic and genetic foundations of the endless chronicle of invasions and extinctions that punctuate evolution. In short, evolutionary game theory describes when to escalate a conflict, how to elicit cooperation, why to expect a balance of the sexes, and how to understand natural selection in mathematical terms.

"...something for anyone interested in game models in organismal biology." Nature"The book under review is a very nice further development of its ten-year-old predecessor...by the authors. Not only has the title been modified, but also the contents have been thoroughly reworked and thus adapted to today's topics of interest in the field of biomathematics. The book is totally restructured and contains much new material, mainly in game theory, especially in its evolutionary and dynamical aspects...the book is written in the well-known authors' usual clear, elegant and motivating style." Mathematical Reviews"The book under review is a very nice further development of its ten-year-old predecessor...by the authors. Not only has the title been modified, but also the contents have been thoroughly reworked and thus adapted to today's topics of interest in the field of biomathematics. The book is totally restructured and contains much new material, mainly in game theory, especially in its evolutionary and dynamical aspects...this book is written in the well-known authors' usual clear, elegant and motivating style." Mathematical Reviews"For the biologist who is mathematically inclined or the mathematician interested in biology...this volume is rich in results and likely to provoke stimulating thought." The Quarterly Review of Biology

How to understand evolution in mathematical terms, i.e. how to model natural selection by game theory.

This title explains how to understand evolution in mathematical terms, i.e. how to model natural selection by game theory.

This textbook is an introduction to dynamical systems and its applications to evolutionary game theory, mathematical ecology, and population genetics. This first English edition is a translation from the authors' successful German edition which has already made an enormous impact on the teaching and study of mathematical biology. The book's main theme is to discuss the solution of differential equations that arise from examples in evolutionary biology. Topics covered include the Hardy-Weinberg law, the Lotka-Volterra equations for ecological models, genetic evolution, aspects of sociobiology, and mutation and recombination. There are numerous examples and exercises throughout and the reader is led up to some of the most recent developments in the field. Thus the book will make an ideal introduction to the subject for graduate students in mathematics and biology coming to the subject for the first time. Research workers in evolutionary theory will also find much of interest here in the application of powerful mathematical techniques to the subject.

Since the work of Maynard Smith and others, it has been realised how game theory can model natural selection. Evolutionary game theory replaces the concept of rational players with the population dynamics of behavioural programs and can be used to understand the strategic and genetic foundations of the endless chronicle of invasions and extinctions which punctuate evolution. In short, it describes when to escalate a conflict, how to elicit cooperation, why to expect a balance of the sexes, and how to understand natural selection in mathematical terms.

Includes bibliographical references (p. 301-320) and index.

Introduction for game theorists; Introduction for biologists; Part I. Dynamical Systems And Lotka-Volterra Equations: 1. The logistic equation; 2. Lotka-Volterra for predator-prey systems; 3. Lotka-Volterra for two competitors; 4. Ecological equations for two species; 5. Lotka-Volterra for more than two populations; Part II. Game Dynamics And Replicator Equations: 6. Evolutionarily stable strategies; 7. Replicator equations; 8. Other game dynamics; 9. Adaptive dynamics; 10. Asymmetric conflicts; 11. More on bimatrix games; Part III. More On Lotka-Volterra And Replicator Dynamics: 12. Hypercircles and permanence; 13. Criteria for permanence; 14. Replicator networks; 15. Stability in n-species communities; 16. Some low-dimensional ecological systems; 17. Heteroclinic cycles and C-matrices; Part IV. Population Genetics: 18. Discrete dynamical systems in population genetics; 19. Continuous selection dynamics; 20. Mutation and recombination; 21. Fertility selection; 22. Game dynamics for Mendelian populations; Bibliography; Index.