Course: Math 454, Game Theory, Spring 2026
Recommended Prerequisite: 1 from [Math 407 or Math 307] and 1 from [Math 225 or Math 235].
Course Content: This course will present the mathematics of game theory, i.e. the quantitative modeling of strategic interaction. Topics include: impartial games, partisan games, zero sum games, von Neumann's Minimax Theorem, general sum games, Nash equilibrium, fixed point theorems, evolutionary game theory, signaling, coalitions, auctions, and social choice theory. Time permitting, we will cover quantum games, algorithmic game theory, bandit problems, reinforcement learning or Monte Carlo Tree Search. The target audience of this course is advanced undergraduate students in mathematics, economics, computer science, or related fields, with an interest in a mathematically focused course on game theory.
Last update: 10 October 2024

Instructor: Steven Heilman, stevenmheilman(@-symbol)gmail.com
Office Hours: Fridays, 1015AM-11PM, Mondays, 12PM-1PM, KAP 406G
Lecture Meeting Time/Location: Mondays, Wednesdays, and Fridays, 11AM-1150PM, DMC 157
TA: TBD, tbd@usc.edu(@-symbol)usc.edu TA Office Hours: held in the Math Center
Discussion Section Time/Location: Tuesdays, 1PM-150PM, THH 215

Textbook: The following textbook is recommended but not required.
Karlin and Peres, Game Theory, Alive.
Some other non-required textbooks: Game Theory, Maschler, Solan and Zamir. Compared to the book of Karlin-Peres, this book is larger and more comprehensive. However, it is also a more advanced textbook, so it might be difficult to read if you have not taken several advanced math classes. See also the A course in game theory book of Thomas S. Ferguson

Exam 1: Wednesday, February 18, 11AM-1150AM, DMC 157
Exam 2: Friday, March 27, 11AM-1150PM, DMC 157
Final Exam: Wednesday, May 6, 11AM-1PM, DMC 157
Other Resources: An introduction to mathematical arguments, Michael Hutchings, An Introduction to Proofs, How to Write Mathematical Arguments

Email Policy:

Extra Credit Project: There will be an optional extra credit project, where students will create a computer program that plays Nash's game of Hex in Python, and the top performers of a tournament will be awarded around 1% to 3% extra credit points for the course. The project would be due in the last week of class, and the ``finals'' of the tournament would occur in class during this time as well. Students can work in groups of up to three, and if a team wins some amount of extra credit, that credit will be split evenly among the participants. Since I will be running the finals on a Microsoft Surface Tablet (without much memory or processing power), you should not use too many extra Python packages beyond some standard ones. The code defining the game is HERE. The code is currently set up so that player 1 is playing a "blocking" type of strategy, while player 2 is just making random available moves. Your first task is to build a program that can beat player 1's blocking type strategy, in at least, say, 80 percent of games, while your program acts as the second player.

Exam Procedures: Students must bring their USCID cards to the midterms and to the final exam. Phones must be turned off. Cheating on an exam results in a score of zero on that exam. Exams can be regraded at most 15 days after the date of the exam. This policy extends to homeworks as well. All students are expected to be familiar with the USC Student Conduct Code. (See also here.)
Accessibility Services: If you are registered with accessibility services, I would be happy to discuss this at the beginning of the course. Any student requesting accommodations based on a disability is required to register with Accessibility Services (OSAS) each semester. A letter of verification for approved accommodations can be obtained from OSAS. Please be sure the letter is delivered to me as early in the semester as possible. OSAS is located in 301 STU and is open 8:30am-5:00pm, Monday through Friday.
https://osas.usc.edu/
213-740-0776 (phone)
213-740-6948 (TDD only)
213-740-8216 (fax)
OSASFrontDesk@usc.edu

Discrimination, sexual assault, and harassment are not tolerated by the university. You are encouraged to report any incidents to the Office of Equity and Diversity http://equity.usc.edu/ or to the Department of Public Safety http://capsnet.usc.edu/department/department-public-safety/online-forms/contact-us. This is important for the safety whole USC community. Another member of the university community - such as a friend, classmate, advisor, or faculty member - can help initiate the report, or can initiate the report on behalf of another person. The Center for Women and Men http://www.usc.edu/student-affairs/cwm/ provides 24/7 confidential support, and the sexual assault resource center webpage sarc@usc.edu describes reporting options and other resources.

Exam Resources: Here are the exams and solutions I used when I last taught this class: Exam 1 Exam 1 Solution Exam 2 Exam 2 Solution Final Final Solution Exam 1, Exam 1 Solution, Exam 2, Exam 2 Solution, Final, Final Solution, Exam 1, Exam 1 Solution, Exam 2, Exam 2 Solution, Final, Final Solution, Here is a page containing practice exams for another game theory class. Here is a page containing practice exams for another game theory class. Here is a page containing a practice midterm for another game theory class. Here is a page containing a practice final for another game theory class. Occasionally these exams will cover slightly different material than this class, or the material will be in a slightly different order.


Homework Policy:

Grading Policy:

Tentative Schedule: (This schedule may change slightly during the course.)

Week Monday Tu Wednesday Thursday Friday
1 Jan 12: 1.1, Impartial Games Jan 14: 1.1.1, 1.1.2, Chomp, Nim Jan 15: Jan 16: 1.1.3, Sprague-Grundy Theorem
2 Jan 19: No class Jan 21: 1.2, Partisan Games Jan 22: Homework 1 due Jan 23: 1.2.1, Hex
3 Jan 26: 2.1, Two-Person Zero Sum Games Jan 28: 2.2, Minimax Theorem, Background Jan 29: Jan 30: 2.2, Minimax Theorem
4 Feb 2: 2.3, Domination Feb 4: 3.1, General Sum Games Feb 5: Homework 2 due Feb 6: 3.2, Nash equilibria
5 Feb 9: 3.3, Correlated equilibria Feb 11: 3.6, Fixed Point Theorems Feb 12: Feb 13: 3.5, Nash's Theorem
6 Feb 16: No class Feb 18: Midterm #1 Feb 19: No homework due Feb 20: 3.7, Evolutionary Game Theory
7 Feb 23: 3.8, Signaling and Asymmetric Information Feb 25: 4.1, Coalitions and Shapley Value Feb 26: Homework 3 due Feb 27: 5.1, Mechanism design
8 Mar 2: 5.2, Auctions Mar 4: 5.2, Auctions Mar 5: Mar 6: 6.1, 6.2, Social Choice
9 Mar 9: 6.3, Arrow's impossibility theorem Mar 11: Influences, Fourier analysis Mar 12: Homework 4 due Mar 13: Noise Sensitivity
10 Mar 16: No class Mar 18: No class Mar 20: No class
11 Mar 23: Quantum Games Mar 25: CHSH inequality, Bell's inequality Mar 26: No homework due Mar 27: Midterm #2
12 Mar 30: Algorithmic Game Theory Apr 1: Algorithmic Game Theory Apr 2: Homework 5 due Apr 3: Complexity of Nash Equilibria
13 Apr 6: Complexity of Nash Equilibria Apr 8: Complexity of Nash Equilibria Apr 9: Apr 10: Price of Anarchy
14 Apr 13: Bandits and Reinforcement Learning Apr 15: Bandits and Reinforcement Learning Apr 16: Homework 6 due Apr 17: Bandits and Reinforcement Learning
15 Apr 20: Reinforcement Learning Apr 22: Reinforcement Learning Apr 23: Apr 24: Leeway
16 Apr 27: Leeway Apr 29: Leeway Apr 30: Homework 7 due May 1: Review of Course

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Homework

Homework .tex files

Supplementary Notes