# What does the agent in reinforcement learning exactly do?

What is an agent in reinforcement learning (RL)? I think it is not the neural network behind. What does the agent in RL exactly do?

In order to make that decision, the agent is allowed to use any observation from the environment, and any internal rules that it has. Those internal rules can be anything, but typically in RL, it expects the current state to be provided by the environment, for that state to have the Markov property, and then it processes that state using a policy function $$\pi(a|s)$$ that decides what action to take.