[Syllabus] EECS 692: Advanced Artificial Intelligence

EECS 692: Advanced Artificial Intelligence

Instructor: Joyce Chai

Course Description

Exploration of advanced topics in Artificial Intelligence, focusing on the intersection of language, vision, machine learning, decision making, and cognitive modeling towards embodied AI agents that can communicate, learn, reason, perceive, and act. Emphasis on research methods and practice, through analysis of current literature, replication of published findings, and discussion of research challenges and opportunities. Coursework comprises extensive reading and writing assignments, presentations, and a term project.

Text book

No text book. All course materials (recent publications, homework assignments, etc.) will be available on the class google drive.


  • EECS492/592 is required; EECS595 is optional but highly recommended
  • Knowledge and experience in deep learning and differentiable programming

Schedule of Topics

Introduction to Embodied AI
LLM and Generative AI
Language and Vision
Commonsense Reasoning
Instruction Following
Theory of Mind
Decision Making
Multi-agent Communication
RL with Human Feedback
Meta learning
Continual learning
Explainable AI
Ethics and Fairness

Course Policies


Homework must be turned in on the date that it is due, by 11:59 pm. The homework must be submitted electronically using Canvas and we will use the later timestamp to validate turn-in time. It is your responsibility to ensure that the homework has been uploaded successfully by the due date. Homework that is incorrectly uploaded will be subject to the associated late penalty. Late homework will be penalized 10% per day. Homework turned in after three days will not be accepted.

Office Hours

The instructor will have regularly scheduled office hours each week. You are encouraged to make use of these to discuss aspects of the course including lecture material and homework problems. In cases where you cannot make office hours, contact the instructor to arrange an appointment.


We will use Piazza to facilitate collaborative problem solving between students. It does not serve as constant on-demand access to the instructor. If you have pressing concerns, make sure to ask during the class or office hours.

Academic Honesty

Honor code

All homework submitted must be your own work. Review the College of Engineering’s Honor Code here: http://www.engin.umich.edu/college/academics/bulletin/rules (Links to an external site.)

Special Accommodations

If you have disabilities or medical conditions that require some form of accommodations, please contact the instructor and the Office of Students with Disabilities at the start of the term so that arrangements can be made to accommodate you.

Note: The instructor reserves the right to modify course policies and the course calendar according to the progress and needs of the class.