I'm following along with Berkeley's CS 285 Deep Reinforcement Learning as the start of a self-guided study into Reinforcement Learning. This post has the notes I pulled from the lecture slides and videos as well as my work and thoughts on the homework. The notes are a mixture of figures from the lecture slides and hints and details from the video lectures, written so that I can skim them later to review.