Designing autonomous decision making systems is one of the longstanding goals of Artificial Intelligence. Such decision making systems, if realized, can have a big impact in machine learning for robotics, game playing, control, health care to name a few. This course introduces Reinforcement Learning as a general framework to design such autonomous decision making systems. By the end of this course, you will have a solid knowledge of the core challenges in designing RL systems and how to approach them.
This course will be offered in English. However, the students in this course can submit in English or French any written work that is to be graded.
Quebec university students from outside Polytechnique Montreal can register for the course via Inter-University Transfer Authorization.
Please note that I will also be teaching Machine Learning (ML) (INF8245E) this Fall. You can take both the courses (ML and RL) in parallel.
If you are a student at Poly, UdeM, HEC, McGill, or Mila, then you can request to audit this course by filling this Google Form.
Wednesdays 9:30 am to 12:30 pm
This course is structured to be an in-person course. However, you can join remotely if you cannot attend in-person.
The official slots for lab sessions for this course are either Tuesdays 8:30 am to 11:30 am biweekly or Fridays 2:45 pm to 5:45 pm biweekly depending on your group. However, we will not do regular labs during these slots. We will have few online tutorials during these timeslots. You can use the rest of the lab time to work on the practical assignments by yourself. Additionally, we will have one-hour office hours every day from Monday to Friday where students can ask TAs their doubts about the practical assignments.
|Priyesh Vijayan||Monday||2.00 PM to 3.00 PM||Google Meet Link|
|Dongyan Lin||Tuesday||9.00 AM to 10.00 PM||Google Meet Link|
|Sarath Chandar||Wednesday||12:30 PM to 1:30 PM||M-3406|
|Michael Ma||Thursday||3.00 PM to 4.00 PM||Google Meet Link|
|Xutong Zhao||Friday||5.00 PM to 6.00 PM||Google Meet Link|