RL(Reinforcement learning) – An agent takes actions, and learns by maximizing the reward.
Deep RL – The model for an agent to take action is formed by a deep neural network. This enables the agent to have more complex behaviors.
IRL (Inverse Reinforcement learning) – An agent learns the reward function from the experiences.
An easy-to-understand example: