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"This book collects the essential existing results in thefast-paced field of learning and evolutionary game theory togetherwith new work by two leaders in the field. It will be essential toanyone doing theoretical work on learning and games or usingevoultionary game theory in applied work." Larry Samuelson , Antoine Augustin Cournot Professor of Economics, University of Wisconsin
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In economics, most noncooperative game theory has focused on equilibrium in games, especially Nash equilibrium and its refinements. The traditional explanation for when and why equilibrium arises is that it results from analysis and introspection by the players in a situation where the rules of the game, the rationality of the players, and the players' payoff functions are all common knowledge. Both conceptually and empirically, this theory has many problems.In The Theory of Learning in Games Drew Fudenberg and David Levine develop an alternative explanation that equilibrium arises as the long-run outcome of a process in which less than fully rational players grope for optimality over time. The models they explore provide a foundation for equilibrium theory and suggest useful ways for economists to evaluate and modify traditional equilibrium concepts.
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3 reviews
19 of 25 people found the following review helpful
Good book
27 July 2000
Format:Hardcover
During the work on my master thesis ("Learning in strategic games") i bought several books about the topic. This is the one of them. Chapters 1 and 2 (Introduction, Fictitious Play) are really good introduction into the subject. The following chapters evolve the theory further giving some good ideas for practical implementation (I was writing a C program which had to be able to play the game and to learn). I would recommend this book to anyone interested in relatively new field - Learning in games.
7 of 9 people found the following review helpful
Learning Learning in Games
28 Jan 2003
Format:Hardcover
An excellent treatise on some important work in the theory of learning in games. Fudenberg and Levine provide a good coverage of standard myopic play dynamics with a special emphasis on ficticious play and replicator dynamics. I particularly liked the sections going through the Kandori, Mailath and Rob (1993) model as well as Young (1993) on the evolution of convention.
The treatments of dynamic systems analysis, elementary game theory, stochastic approximation theory, etc., are necessarily short. The appendices do not suffice for a reader without a reasonable background.
Nonetheless an essential read for anybody doing serious work in learning, or wanting to know what all the fuss is about.
7 of 18 people found the following review helpful
This book is not about learning but the application of nonlinear dynamics
2 Sep 2005
Format:Hardcover
This book does not provide valuable information about learning systems. It demonstrates, that nonlinear dynamics can be used to describe a subclass of learning. I personally doubt, that this subclass is of great interest, because it neglects completely heuristic strategies in game playing. Besides this, nonlinear dynamics is only useful if the number of parameter of the system is small. I doubt, that these toy examples are sufficient to describe reality, e.g., economics.
Moreover, the organization of the book and the style it is written in, is in my view not favorable.
I guess, this book is for a very small readership that does not have to worry about the correspondence of a model with nature. But also from this perspective it can not be recommended, because it is not written well. Both thumbs down!
Moreover, the organization of the book and the style it is written in, is in my view not favorable.
I guess, this book is for a very small readership that does not have to worry about the correspondence of a model with nature. But also from this perspective it can not be recommended, because it is not written well. Both thumbs down!
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