CSE 5820: Reinforcement Learning

CSE 5820
Reinforcement Learning

Course Schedule

(Tentative schedule for the course and deviations may be necessary as the course progresses.)

Date	Topic	Notes	Reading (Textbook or Other Materials)
Jan. 20	Introduction		RL: Chapter 1, Nature, Basic calculus refresher
Jan. 22	Machine Learning Basics	HW1 Q5	Machine learning math essentials
Jan. 29	Sequential Decision Making		RL: Chapter 1
Feb. 3	Markov Decision Processes (MDP)	Project Details	RL: Chapter 3
Feb. 5	MDP Bellman Equations		RL: Chapter 3
Feb. 10	Policy Iteration, Value Iteration		RL: Chapter 4
Feb. 12	Model-free Prediction: MC vs. TD		RL: Chapter 5,6,7
Feb. 17	Model-free Control: SARSA, Q-Learning		RL: Chapter 6
Feb. 26	Function Approximation: Linear Classifiers		RL: Chapter 9
Mar. 3	Computational Graphs, Backpropagation		DL: Chapter 8
Mar. 5	Neural Networks, MLP
Mar. 10	Convolutional Neural Networks		AlexNet, ResNet
Mar. 12	Recurrent Nerual Networks, LSTM
Mar. 24	Transformer		Attention is all you need, tutorial
Mar. 26	Deep Q Network (DQN)
Mar. 31	Policy Gradient