prakhardogra921/Monte-Carlo-Methods-for-Reinforcement-Learning

Implementations of many Monte Carlo (MC) algorithms for updating policies of an environment using action values, greedy and epsilon-greedy procedures. Environment used for this notebook is the BlackJack Environment (can be seen in the OpenAI Gym library) and these functions can be used for other environments as well.

Jupyter Notebook