SC 631 – GAMES AND INFORMATION

Course offered in:

Autumn 2017

Instructors:

Prof. Ankur Kulkarni

Course Content:

How to win minds using rigor? How to put people into situations in which they act according to you, but they feel like they are doing what’s best for them? These questions are potentially observed by game theory. This course follows a rigorous treatment of how decisions are made by both individuals and firms based on the information they have.

Basics of static games: Normal form of games. Zero-sum and non-zero sum games, concept of Nash equilibrium. Information: Extensive form of games and information sets. Imperfect, incomplete, and asymmetric information. Stackelberg equilibrium. Bayesian Nash equilibrium. Aumann’s common knowledge. General formulation of dynamic games: subgame perfectness, open-loop, closed-loop and feedback. Nash equilibria, informational properties of Nash equilibria, informational nonuniqueness. Asymmetric information: Moral hazard. Importance of common knowledge. Dynamic stochastic team problems: introduction, information structures (static and dynamic) person-by-person optimality, Witsenhausen problem, signalling, connections to economics, information theory.

Prerequisites:

A course in optimization, such as SC 607, AE 310, EE 659, IE 501, IE 601 or consent of instructor.

Feedback on Lectures:

The lectures were very interesting and interactive.

Feedback on Tutorials, Assignments and Exams:

This course had only the end sem exam which was of medium level of difficulty. All the concepts taught in the class and through the assignments over the course of the semester were used.

Assignments: 40 %

Lecture Notes scribe: 10%

Endsem: 50 %

Assignments helped a lot in grasping the concept taught in lectures and had good questions. Exams were upto the point and completely based on taught syllabus only.

Grading Statistics:

Please have a look on ASC for the same.

Study Material and References:

  • Başar and G. Olsder, Dynamic Noncooperative Game Theory, SIAM, 1999.

  • Fudenberg and Tirole, Game Theory, Ane Books, 2010 (Indian ed).

  • Rasmusen,Games and Information: An Introduction to Game Theory. Wiley-Blackwell, 2006.
  • J. Osborne and A. Rubinstein. Course in Game Theory . MIT Press, 1994
  • Yuksel and T. Başar,Stochastic Networked Control Systems – Stabilization and Optimization under Information Constraints. Birkhäuser, 2013.

Takeaways from the course:

This course gives enough introduction to game theory so that one can take up research projects and won’t find trouble regarding the basics while surveying the literature.

Review by – Karan Chadha (karanchadhaiitb@gmail.com)