My notes and codes (in C++) for UCL's reinforcement learning course.
Course site: UCL Course on RL
- Lecture 1: Introduction to Reinforcement Learning
- Lecture 2: Markov Decision Processes
- Lecture 3: Planning by Dynamic Programming
- Lecture 4: Model-Free Prediction
- Lecture 5: Model-Free Control
- Lecture 6: Value Function Approximation
- Lecture 7: Policy Gradient Methods
- Lecture 8: Integrating Learning and Planning
- Lecture 9: Exploration and Exploitation
- Lecture 10: Case Study: RL in Classic Games
- Policy Iteration and Value Iteration - car rental problem
- Sarsa - cliff walking problem
- Sarsa(lambda) - cliff walking problem
- Q-Learning - cliff walking problem