Building blocks of reinforcement learning

Now that we have seen a few examples, let's dig into the building blocks of a reinforcement learning system. Apart from the interaction between the agent and the environment, there are other factors at play here:

A typical reinforcement learning agent goes through the following steps:

• There is a set of states related to the agent and the environment. At a given point of time, the agent observes an input state to sense the environment.
• There are policies that govern what action needs to be taken. These policies act as decision making functions. The action is determined based on the input state using these policies.
• The agent takes the action based on the previous step.
• The environment reacts in a particular way in response to that action. The agent receives reinforcement, also known as reward, from the environment.
• The agent records the information about this reward. It's important to note that this reward is for this particular pair of state...