Reinforcement learning is a type of machine learning. In this, an agent interacts with its environment by producing actions, and learn with the help of feedback. The feedback is given to the agent in the form of rewards, such as for each good action, he gets a positive reward, and for each bad action, he gets a negative reward. There is no any labeled data or supervision is provided to the agent. In RL, the agent continuously does three things(performing actions, changing state, and getting the feedback) to explore the environment.
The popular reinforcement learning algorithms are:
- Q-Learning
- SARSA(State Action Reward State Action)
- Deep Q Neural Network