Strategic Learning and its Limits by H. Peyton Young

Strategic Learning and its Limits

byH. Peyton Young

Hardcover | May 2, 2005

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In this concise book based on his Arne Ryde Lectures in 2002, Young suggests a conceptual framework for studying strategic learning and highlights theoretical developments in the area. He discusses the interactive learning problem; reinforcement and regret; equilibrium; conditional no-regretlearning; prediction, postdiction, and calibration; fictitious play and its variants; Bayesian learning; and hypothesis testing. Young's framework emphasizes the amount of information required to implement different types of learning rules, criteria for evaluating their performance, and alternative notions of equilibrium to which they converge. He also stresses the limits of what can be achieved: for a given type of game anda given amount of information, there may exist no learning procedure that satisfies certain reasonable criteria of performance and convergence. In short, Young has provided a valuable primer that delineates what we know, what we would like to know, and the limits of what we can know, when we try to learn about a system that is composed of other learners.

About The Author

H. Peyton Young is Senior Fellow in Economic Studies and Governance Studies and Co-Director of the Center on Social and Economic Dynamics at the Brookings Institution. He is also Scott and Barbara Black Professor of Economics at Johns Hopkins University and a Member of the Science Steering Committee at the Santa Fe Institute. His main...
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Details & Specs

Title:Strategic Learning and its LimitsFormat:HardcoverDimensions:176 pages, 8.5 × 5.43 × 0.64 inPublished:May 2, 2005Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0199269181

ISBN - 13:9780199269181

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Table of Contents

1. The Interactive Learning Problem2. Reinforcement and Regret3. Equilibrium4. Conditional No-Regret Learning5. Prediction, Postdiction, and Calibration6. Fictitious Play and Its Variants7. Bayesian Learning8. Hypothesis Testing9. Conclusion