Chapter 2 – A Guide to the Gym Toolkit
- The Gym toolkit provides a variety of environments for training the RL agent ranging from classic control tasks to Atari game environments. We can train our RL agent to learn in these simulated environments using various RL algorithms.
- We can create a Gym environment using the
makefunction requires the environment ID as a parameter.
- We learned that the action space consists of all the possible actions in the environment. We can obtain the action space by using
- We can visualize the Gym environment using the
- Some classic control environments offered by Gym include the cart pole balancing environment, the pendulum, and the mountain car environment.
- We can generate an episode by selecting an action in each state using the
- The state space of the Atari environment will be either the game screen's pixel values or the RAM...