Program Overview

Program Description

The MATH 146 course focuses on the emerging interdisciplinary field of game theory and artificial intelligence, providing students with a comprehensive understanding of strategic decision-making, learning dynamics, and cooperative behaviors in AI systems. Through a combination of lectures, discussions, and hands-on projects, the class introduces the fundamental concepts and applications of evolutionary games, repeated games, stochastic games, and multiagent learning systems. The course also covers the ethical implications and alignment mechanisms required to ensure AI systems serve humanity.

Prerequisites

• Math 22
• Math 23
  • The student should be familiar with calculus, and basic concepts in ordinary differential equations and probability.
  • Programming skills are highly recommended, but not required.

Textbook and Grading Formula

• Lecture notes are available.
• The grading formula consists of:
  • Class Participation (10%)
  • Four homework problem sets (40%)
  • Final projects (40%) on topics of your choice
  • Lightning talk based on the project (10%)
• The final project requires a significant component of using quantitative methods and a final report written in the format of a scientific paper.

Integration of ChatGPT

The class welcomes the wise and responsible use of ChatGPT, or Large Language Models (LLMs), as an integral part of experiential learning. There is no penalty for utilizing ChatGPT, but students are required to disclose explicitly by including the prompt history as part of their submission.

Important Dates

• Final project proposal due on: 2 October 2023
• Homework problem sets due biweekly
• Final project presentations: in the week of 6 November 2023
• Final project report due on: 15 November 2023
• Course withdrawal deadlines:
  • 23 October 2023: Final day for dropping a 4th course
  • 31 October 2023: Final day to withdraw from a course

Syllabus

The tentative lecture plan includes:

• Week 1: Introduction & Overview; Introduction to Evolutionary Games and Learning Dynamics
• Week 2: Repeated Games and Machine Learning Based Strategies
• Week 3: Stochastic Games and Reinforcement Learning
• Week 4: Understanding AI Behavior and Moral Characters Through Evolutionary Game Theory
• Week 5: Cooperative AI Systems: Finding Common Ground and Cooperative Social Norms
• Week 6: Multiagent Learning Systems: Seeking Consensus and Convergence and Red Queen Dynamics
• Week 7: Learning and Evolving Populations: Multiscale and Multilayer Network Dynamics
• Week 8: Alignment Mechanisms: Serving All Humanity
• Week 9: Final Projects Presentations

Course Projects and Presentation Schedule

• Approximately 5 weeks are given to complete the project.
• The instructor will suggest project ideas, but students are allowed to propose their own, which must be approved by the instructor.
• Each project presentation is limited to 15 minutes and preferably in the style of TED talks.

Course Policies

Class Recording Notifications to Students

• Consent to recording of course meetings and office hours that are open to multiple students.
• Requirement of consent to one-on-one recordings.

Honor Principle

• Collaborations during closed-book exams and quizzes are strictly prohibited.
• Any form of plagiarism is not allowed in the final project.

Student Accessibility and Accommodations

• Students requesting disability-related accommodations and services are encouraged to schedule a meeting with the instructor.
• In order for accommodations to be authorized, students are required to consult with Student Accessibility Services (SAS).

Student Religious Observances

• If a student has a religious observance that conflicts with their participation in the course, they should meet with the instructor to discuss appropriate accommodations.

Mental Health and Wellness

• The instructor encourages students to use available resources to support their wellness.

Late Policy

• An extension of maximum 4 days will be granted on a case-by-case basis for the final project report, with a penalty of 5% each additional day.