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'This short volume is very welcome . . . Most importantly, on pages 32-33, the volume reprints as an appendix to the journal article based on Nash's Princeton doctoral dissertation on non-cooperative games a section of the thesis on "motivation and interpretation" that was omitted from the article. An editorial note remarks mildly that "The missing section is of considerable interest". This section, not available in any other published source, makes the present volume indispensable for research libraries . . . Nash's Essays on Game Theory, dating from his years as a Princeton graduate student . . . has a lasting impact on economics and related fields unmatched by any series of articles written in such a brief time . . . To economists, his name will always bring to mind his game theory papers of the early 1950s. It is good to have these conveniently reprinted in this volume.' - Robert W. Dimand, The Economic Journal 'The news that John Nash was to share the 1994 Nobel Prize for Economics with John Harsanyi and Reinhard Selten was doubly welcome. It signalled not only that the brilliant achievements of his youth were to be recognized in a manner consistent with their significance, but that the long illness that clouded his later years had fallen into remission. I hope that this collection of his economic papers will serve as another reminder that John Nash has rejoined the intellectual community to which he has contributed so much.' - From the introduction by Ken Binmore Essays on Game Theory is a unique collection of seven of John Nash's essays which highlight his pioneering contribution to game theory in economics. Featuring a comprehensive introduction by Ken Binmore which explains and summarizes John Nash's achievements in the field of non-cooperative and cooperative game theory, this book will be an indispensable reference for scholars and will be welcomed by those with an interest in game theory and its applications to the social sciences.
Recent events in international financial markets have revived the scientific interest in conceivable institutional alternatives to prevailing monetary arrangements. In the essays reprinted in this book, the author critically examines some of the more influential arguments which have been made in favour of decentralization in banking.
The mathematical study of games is an intriguing endeavor with implications and applications that reach far beyond tic-tac-toe, chess, and poker to economics, business, and even biology and politics. Most texts on the subject, however, are written at the graduate level for those with strong mathematics, economics, or business backgrounds. In
Computer science and economics have engaged in a lively interaction over the past fifteen years, resulting in the new field of algorithmic game theory. Many problems that are central to modern computer science, ranging from resource allocation in large networks to online advertising, involve interactions between multiple self-interested parties. Economics and game theory offer a host of useful models and definitions to reason about such problems. The flow of ideas also travels in the other direction, and concepts from computer science are increasingly important in economics. This book grew out of the author's Stanford University course on algorithmic game theory, and aims to give students and other newcomers a quick and accessible introduction to many of the most important concepts in the field. The book also includes case studies on online advertising, wireless spectrum auctions, kidney exchange, and network management.
Andrew Coleman provides an accessible introduction to the fundamentals of mathematical gaming and other major applications in social psychology, decision theory, economics, politics, evolutionary biology, philosophy, operational research and sociology.
​This book both summarizes the basic theory of evolutionary games and explains their developing applications, giving special attention to the 2-player, 2-strategy game. This game, usually termed a "2×2 game” in the jargon, has been deemed most important because it makes it possible to posit an archetype framework that can be extended to various applications for engineering, the social sciences, and even pure science fields spanning theoretical biology, physics, economics, politics, and information science. The 2×2 game is in fact one of the hottest issues in the field of statistical physics. The book first shows how the fundamental theory of the 2×2 game, based on so-called replicator dynamics, highlights its potential relation with nonlinear dynamical systems. This analytical approach implies that there is a gap between theoretical and reality-based prognoses observed in social systems of humans as well as in those of animal species. The book explains that this perceived gap is the result of an underlying reciprocity mechanism called social viscosity. As a second major point, the book puts a sharp focus on network reciprocity, one of the five fundamental mechanisms for adding social viscosity to a system and one that has been a great concern for study by statistical physicists in the past decade. The book explains how network reciprocity works for emerging cooperation, and readers can clearly understand the existence of substantial mechanics when the term "network reciprocity" is used. In the latter part of the book, readers will find several interesting examples in which evolutionary game theory is applied. One such example is traffic flow analysis. Traffic flow is one of the subjects that fluid dynamics can deal with, although flowing objects do not comprise a pure fluid but, rather, are a set of many particles. Applying the framework of evolutionary games to realistic traffic flows, the book reveals that social dilemma structures lie behind traffic flow.
It is widely held that Bayesian decision theory is the final word on how a rational person should make decisions. However, Leonard Savage--the inventor of Bayesian decision theory--argued that it would be ridiculous to use his theory outside the kind of small world in which it is always possible to "look before you leap." If taken seriously, this view makes Bayesian decision theory inappropriate for the large worlds of scientific discovery and macroeconomic enterprise. When is it correct to use Bayesian decision theory--and when does it need to be modified? Using a minimum of mathematics, Rational Decisions clearly explains the foundations of Bayesian decision theory and shows why Savage restricted the theory's application to small worlds. The book is a wide-ranging exploration of standard theories of choice and belief under risk and uncertainty. Ken Binmore discusses the various philosophical attitudes related to the nature of probability and offers resolutions to paradoxes believed to hinder further progress. In arguing that the Bayesian approach to knowledge is inadequate in a large world, Binmore proposes an extension to Bayesian decision theory--allowing the idea of a mixed strategy in game theory to be expanded to a larger set of what Binmore refers to as "muddled" strategies. Written by one of the world's leading game theorists, Rational Decisions is the touchstone for anyone needing a concise, accessible, and expert view on Bayesian decision making.