RL Notes

Rough Notes for Reinforcement Learning.

Largely inspired by Sutton & Barto's RL Book and David Silver's Lectures.

Notes in this repository:

1. Introduction to RL
2. Markov Decision Processes
3. Planning using Dynamic Programming

Implementations:

1. Simple Gridworld
   • Value Iteration
   • Policy Evaluation
   • Policy Iteration
2. BlackJack Game
   • Monte-Carlo Policy Evaluation

TODO:

• Notes on Model-Free Prediction
• Notes on Model-Free Control