(This the 2023 version of the course. If you are taking this course right now, please go to the new website.)
This is the homepage of the course CMPUT 365: Introduction to Reinforcement Learning taught by Csaba Szepesvári at the University of Alberta in the Winter semester of 2023.
You should also be on the course slack workspace (check eClass for the invitation link).
Lecture Date/Location: MWF 1:00 to 1:50 pm at CAB-235
We are linking the notes and the worksheets here for easy access.
Notes: MDPs, Is this an MDP? Pick and Place, Value Functions, Optimality, Dynamic Programming, Derivatives, TD(0) with Linear Function Approximation
Worksheets: W0, W1, W2, W3, W4, W5, W6, W7, W8, W9, W10, W11
If you get have any issues with submitting quizzes, try clearing the internet cache, closing all browser windows, and re-logging again to Coursera.
Jupyter notebook assignments include local tests (included in the notebook), as well as grader tests that is hidden from the learners.
Please make sure your assignment passes all the local tests before submitting. Also, the solutions have to be general (i.e. not hard-coded) in order to pass the grader tests. Local test cases are not comprehensive, and even if you pass all the local tests, you may not get full marks.
Try to make your code general to work robustly for various cases. (e.g. using variable grid_w instead of value 12)
On rare occasion you may face issues submitting jupyter notebook assignments. If the submit button is missing, please make sure you are only working on the notebook on a single device. If the problem still persists, try setting ?forceRefresh=true in your notebook URL (see this reference).