Game Theory

by Drew Fudenberg, Jean Tirole

This advanced text introduces the principles of noncooperative game theory in a direct and uncomplicated style that will acquaint students with the broad spectrum of the field while highlighting and explaining what they need to know at any given point.

This advanced text introduces the principles of noncooperative game theory—including strategic form games, Nash equilibria, subgame perfection, repeated games, and games of incomplete information—in a direct and uncomplicated style that will acquaint students with the broad spectrum of the field while highlighting and explaining what they need to know at any given point. The analytic material is accompanied by many applications, examples, and exercises. The theory of noncooperative games studies the behavior of agents in any situation where each agent's optimal choice may depend on a forecast of the opponents' choices. "Noncooperative" refers to choices that are based on the participant's perceived selfinterest. Although game theory has been applied to many fields, Fudenberg and Tirole focus on the kinds of game theory that have been most useful in the study of economic problems. They also include some applications to political science. The fourteen chapters are grouped in parts that cover static games of complete information, dynamic games of complete information, static games of incomplete information, dynamic games of incomplete information, and advanced topics.
--mitpress.mit.edu

Genres: Economics, Mathematics, Textbooks, Reference, Nonfiction, Finance, Academic

603 pages, Hardcover

First published August 1, 1991

About the author

Drew Fudenberg is Frederick E. Abbe Professor of Economics at Harvard University.

Reviews

[Paola · Rating 4 out of 5]

This has been the standard game theory textbook for graduate students in economics for a very long time. However it is not as clear and precise as either Game Theory. Analysis of conflict or A course in Game Theory. For self study, it may be better to start with something like Ken Binmore's Fun and Games: A Text on Game Theory or Osborne's An Introduction to Game Theory, International Edition

[Richard · Rating 5 out of 5]

My favourite work on Game Theory, an introduction worth the intellectual investment and a book that opens the door to further study. Fudenberg analyzes and refines solution concepts like trembling-hand perfection and proper equilibrium to eliminate non-credible threats in dynamic settings. His work formalizes Subgame Perfect Equilibrium (SPE), Perfect Bayesian Equilibrium (PBE), and Sequential Equilibrium, clarifying how credibility and Bayes' rule update player beliefs over time. He moves beyond the strict assumption of hyper-rationality, modeling equilibrium as the long-run outcome of adaptive learning processes where players adjust strategies over time. Notably, recursive equations and belief tracking make many of his advanced models hard to compute outside simplified environments. This is a work that I have reread many times and will continue to do so in the hope of being able to successfully apply the reasoning contained within to new models. This is a significant undertaking since advanced game theory relies heavily on real analysis, topology, optimization, and advanced probability theory to prove equilibrium existence, model continuous strategies, and handle information asymmetry. Topology and Fixed-Point Theorems are essential for proving that Nash equilibria exist in games with continuous or mixed strategies (using theorems like Kakutani's or Brouwer's fixed-point theorems). Real Analysis and Measure Theory are used to analyze games with infinite strategy spaces, continuous payoff functions, and rigorous probability spaces. Advanced Probability and Stochastic Processes are required for Bayesian games, incomplete/imperfect information models, and dynamic stochastic games (including Markov decision processes). Optimization and Mathematical Programming are applied to mechanism design, auction theory, and linear/dynamic programming to find optimal strategies and incentive-compatible rules. Differential Equations are used in differential games and evolutionary game theory to model continuous changes in strategies over time or across populations. While Combinatorics and Graph Theory are utilized in cooperative game theory, network games, and combinatorial games with perfect information.

[May Ling · Rating 3 out of 5]

Not bad. It goes through the basics of Game theory with each chapter adding onto the prior. It goes through tons of examples. It is quite applicable to finance related topics, not sure for those that are not into that whether it would be as helpful. Then again, I think the most aggressive use of this type of mathematics would be finance at this point in time.

I would recommend it as a text book. There is also an e-book version, but I suspect that it is better to have the hard copy for something of this nature.

[Temuulen · Rating 5 out of 5]

goat text on GT.

[dameolga]

A friend told me about this book and loaned it to me for a few weeks. I unfortunately didn't have much free time to look at it, but Fudenberg and Tirole's book covered an array of game theoretical topics and in a more mathematical approach than Dixit's Games of Strategy. I really want to get my hands on this book to keep.

[Don · Rating 5 out of 5]

This is the book to own if you want to be a theorist.

[Tista Kundu]

tough a bit