CS 639 section 006: Topics in Game Theory and Learning (Fall 2025)

Overview: Game theory is a mathematical framework to study interactions between multiple strategic agents, 
where agents view these interactions as "games" they are trying to "win". Mechanism design studies the design 
of such interactions so as to obtain socially desirable outcomes. Machine learning deals with growing experience 
by playing games.  In this class, we introduce these topics and connect them through the lens of a computer scientist. 
This class is primarily targeted towards advanced undergraduate and early graduate students with a strong background 
in mathematics and algorithms.

Lectures: Tu, Th 9:30-10:45 in ENGR HALL 2255
Instructor: Professor Jerry Zhu, jerryzhu@cs.wisc.edu
Office hours: Thursdays 4-5pm in Morgridge Hall 5520

Prerequisites: CS240, CS475, Econ301, or Econ 311.  We will use tools from calculus, probability, statistics, 
optimization, algorithms, and machine learning.  It is the student's responsibility to have an adequate background 
in these areas.  Students are expected to be comfortable with mathematical proofs and logical reasoning.

Textbook (available online): 
   Game Theory, Alive by Anna Karlin and Yuval Peres, denoted KP below. 
   Tim Roughgarden's lecture notes on Algorithmic Game Theory

Discussions: piazza

Last year's schedule, to be updated
introduction (KP 2.1)
two-player zero sum games, Von Neumann's minimax theorem (KP 2.2-2.6)
Nash equilibrium, linear program (KP appendix A)
general-sum games (KP 4-4.3, 4.5), dominant strategy (KP 2.4.3)
potential games, best response dynamics (KP 4.4)
extensive form games, imperfect and incomplete information (KP 6)
correlated equilibrium (KP 7.2, R lecture 13 section 3)
in-class midterm, the price of anarchy and stability (KP 8)
cooperative games, the Sharpley value (KP 12-12.3)
auction (KP 14.1, 14.2)
VCG (KP 15.1-15.4, 16.1, 16.2)
evolutionary game theory (KP 7.1, 18.1)
no-regret learning (KP 18.3)
minimax theorem (KP 18.4)

Grading: Class participation: 20%, Midterm exam: 40%, Final exam: 40%.

Midterm exam: in-class on Tuesday Oct. 21, 2025.

Final exam: TBD by the university

A make-up exam will be offered only for documented emergencies and travel to academic conferences. The decision to accommodate a make-up exam will be at the discretion of the instructor.

Please read the university's policy on academic misconduct.