I'm confused with the two terminology - action and policy - in Reinforcement Learning. As far as I know, the action is:
It is what the agent makes in a given state.
However, the book I'm reading now (Hands-On Reinforcement Learning with Python) writes the following to explain policy:
we defined the entity that tells us what to do in every state as policy.
Now, I feel that the policy is the same as the action. So what is the difference between the two, and how can I use them apart correctly?