Game Theory

Knowledge

Required Prior Knowledge

Some parts of the course use elementary high-school math (for example solving equations or working with simple derivatives). The course, however, focuses mainly on the concepts of the game theory.

Description

Game theory is a scientific field that aims to make sense of strategic decision-making. The field has broad applications in a variety of social contexts, such as in bargaining, negotiations, collaborations, and competitive relationships. In this course, students learn how to translate real-world social interactions into formal game theory models. In a follow-up step, students are then exposed to different techniques of how to analyze these games: by identifying the game's equilibria, by running individual-based simulations, or by employing controlled lab experiments with human participants.

Learning objectives

After successfully completing the course, students will be able to

•    Describe how to understand social interactions through the lens of game theory. This requires identi-fying the relevant players, their possible actions, the information they have, and their incentives to choose different actions
•    Predict behavior in these different games by either computing their equilibria, or by simulating how indi-viduals might learn how to play strategically
•    Assess these theoretical predictions with empirical data on human behavior in strategic/social interactions

Comment

Content:

•    Overview on different classes of games (simultaneous versus sequential decision-making, complete versus incomplete information)
•    Appropriate solution concepts (Nash equilibrium, backward induction, Bayesian Nash equilibrium)
•    Learning in games and evolutionary dynamics
•    Comparison to empirical/experimental data