This course begins with an introduction to game theoretic analysis. We study the concepts and models used to analyze strategic behavior, including normal and extensive form games, games of incomplete information, finite and infinitely repeated games, auctions, and mechanism design. We then review recent advances in computer science in the development of algorithms to analyze these problems, and to design a better world. Finally, we explore applications of algorithmic game theory to the development of AI; to structuring social interactions in markets and on the Internet; and to the future of social science research. This course requires as a prerequisite Mathematics for Data Science or a similar course, in particular a working knowledge of multivariate calculus and optimization. The course will occasionally rely on some methods of mathematical proof (e.g., proof by contradiction, proof by induction, etc.), but prior exposure to them is not assumed.
Instructor
- Asya Magazinnik , Professor of Social Data Science