Game Theory & Behavior Jeffrey Carpenter & Andrea Robbett MIT Press, mid-2022
The primary goal of this book is to provide a clear and accessible formal introduction to standard game theory, while at the same time addressing how people actually behave in these games and explaining how the standard theory can be expanded or updated to better predict the behavior of real people. Our objective is to simultaneously provide students with both the theoretical tools to analyze situations through the logic of game theory and the intuition and behavioral insights to apply these tools to real world situations. The book was written to serve as the primary textbook in a first course in game theory at the undergraduate level and does not assume students have any previous exposure to game theory or economics. However, the book may also be a useful resource for graduate students or researchers who are looking for a synthesis of behavioral research or a concise introduction to some of the advanced topics covered, such as cooperative game theory, matching market design, social dilemmas, voting games, quantal response equilibrium, level-k reasoning or psychological game theory.
Most chapters follow the same basic format: We begin each chapter with a motivating game, which sets up the topic. The reader is then be asked what they should (or would) do in this situation. We provide protocols and supplementary materials for instructors who want to run the motivating game for each chapter as an experiment during class, enabling students to learn experientially and build their intuition before diving in. From there, the chapter provides a traditional game theoretic analysis of these types of games. We then present data from similar lab experiments, discuss when the predictions are likely to hold, and summarize the main behavioral insights. But, to the extent that behavior deviates from the predictions, we emphasize that this is not the end of the story and doesn't imply that we should give up on game theory as a framework for understanding strategic interactions. Instead, we explain how these insights about human behavior have been woven back into the theory to better predict behavior of real people, for example using social preference models, quantal response equilibrium, level-k reasoning, cursed equilibrium, and so on. The goal is to demonstrate that a positive treatment of game theory, one that stresses the iterative process of advancing theory and gathering data, leads to more accurate predictions.
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