This is a repo containing explanations and implementations of the following Reinforcement Learning algorithms. Note that, if you want to see the notebooks clearly (with LaTeX and stuff) you need to clone the repo.

• git clone [email protected]:ceteke/RL.git
• cd RL
• jupyter notebook

The tabular methods are demonstrated on OpenAI Gym's FrozenLake environment.

• Policy Iteration
• Value Iteration

• On-Policy Control
• Exploring Starts
• Off-Policy Control

• On-Policy TD (Sarsa)
• Off-Policy TD (Q-Learning)
• n-Step On-Policy TD (Sarsa)

• Linear Sarsa
• Average Reward Linear Sarsa
• n-Step Linear Sarsa
• Actor-Critic Action Value Policy Gradient

• REINFORCE (Monte Carlo Policy Gradient)
• Hindsight Experience Replay