Algorithmic Game Theory

CS60025, Autumn 2026, LTP: 3-0-0


Instructor Somindu Chaya Ramanna
Teaching assistant Golla Meghanandh Manvith Prabhash
Classes THUR: 15:00-16:55; FRI: 15:00-15:55 at CSE-302
Tutorials on Saturdays

Notices and Announcements

Prerequisites

I assume familiarity with probability theory, discrete mathematics and algorithms. These topics will not be covered in the course. No prior knowledge of game theory is required.

Evaluation Plan (tentative)

Teacher's Assessment     40%   [30% Class Tests/Quizzes + 10% Attendance]
Mid-Semester Examination     30%
End Semester Examination     30%

Lectures

Week Date Topics Covered
1 23 July Introduction to Game Theory, Normal Form Games, Examples
24 July Dominant Strategy Equilibria (Strong/Weak/Very Weak Dominance), WDSE for Second-Price Auctions
2 30 July Nash Equilibrium: PSNE, MSNE, Examples
Necessary and Sufficient Condition for MSNE
31 July Matrix Games: Examples, Saddle Points, PSNE and Saddle Points
Mixed Strategies, Minmaximisation and Maxminimisation
3 6 August Optimisation Problems for the 2 Players, Equivalent LPs
Minimax Theorem, Implications on MSNE for Matrix Games
(Look at reference no. 6 for an exposition on linear programming)
7 August Application of the max-min inequality for matrix games: Yao's Lemma

References

  1. Lecture Notes on Algorithmic Game Theory (CS60025) by Palash Dey (available here).

  2. Course on Algorithmic Game Theory -- Lecture Notes by Tim Roughgarden (available here).

  3. Algorithmic Game Theory, Edited by Nisan, Roughgarden, Tardos and Vazirani, Cambridge University Press, 2007 (available for free from here).

  4. Game Theory by Michael Maschler, Eilon Solan, and Shmuel Zamir.

  5. Game Theory and Mechanism Design by Y. Narahari (equivalent lecture notes are available here).

  6. Combinatorial Optimization: Algorithms and Complexity by Christos H. Papadimitriou and Kenneth Steiglitz.