[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.
Prerequisite
- EECS492/592 is required; EECS595 is optional but highly recommended
- Knowledge and experience in deep learning and differentiable programming
Schedule of Topics
| Topics |
|---|
| Introduction to Embodied AI |
| Benchmarks |
| 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
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.
Piazza
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.