I am currently reading "Reinforcement Learning" from Sutton & Barto and I am attempting to write some of the methods myself.
Policy iteration is the one I am currently working on. I am trying to use OpenAI Gym for a simple problem, such as CartPole or continuous mountain car.
However, for policy iteration, I need both the transition matrix between states and the Reward matrix.
Are these available from the 'environment' that you build in OpenAI Gym.
I am using python.
If not, how do I calculate these values, and use the environment?