The anatomy of the agent
As you learned in the previous chapter, there are several entities in RL's view of the world:
- The agent: A thing, or person, that takes an active role. In practice, the agent is some piece of code that implements some policy. Basically, this policy decides what action is needed at every time step, given our observations.
- The environment: Some model of the world that is external to the agent and has the responsibility of providing observations and giving rewards. The environment changes its state based on the agent's actions.
Let's explore how both can be implemented in Python for a simple situation. We will define an environment that will give the agent random rewards for a limited number of steps, regardless of the agent's actions. This scenario is not very useful, but it will allow us to focus on specific methods in both the environment and agent classes. Let's start with the environment:
class Environment:
...
