RL-course

This Reinforcement Learning course covers fundamental topics in sequential decision-making under uncertainty.

The author is primarily inspired by the excellent Practical_RL course, which he studied at YSDA. The practical assignments and homeworks are adapted and extended from the materials presented in the Practical RL course.

Other sources of inspiration include:

1. DeepMind Reinforcement Learning Lecture Series 2021
2. Sutton & Barto book
3. Introduction to Reinforcement Learning with David Silver
4. Reinforcement Learning Textbook
5. Reinforcement Learning: An Overview