The Python library called Gym
was developed and has been maintained by OpenAI (www.openai.com). The main goal of Gym is to provide a rich collection of environments for RL experiments using a unified interface. So, it's not surprising that the central class in the library is an environment, which is called Env
. It exposes several methods and fields that provide the required information about an environment's capabilities. From high level, every environment provides you with these pieces of information and functionality:
A set of actions that are allowed to be executed in an environment. Gym supports both discrete and continuous actions, as well as their combination.
The shape and boundaries of the observations that an environment provides the agent with.
A method called
step
to execute an action, which returns the current observation, reward, and indication that the episode is over.A method called
reset
to return the environment to its initial state and to obtain the first observation...