DRL

Reinforcement Learning

AI, ML
AI, ML, Reinforcement Learning, DRL

Reinforcement Learning #

Reinforcement Learning (RL) is a learning approach in which an agent improves its behaviour by interacting with an environment and observing the rewards produced by its actions.

Unlike supervised learning, the agent is not given a correct action label for every situation. It must discover useful behaviour through trial, feedback, and repeated interaction.

Reinforcement learning is goal-oriented learning through interaction.

Why Reinforcement Learning? #

RL is useful when decisions affect what happens next and the quality of an action may only become clear later.