Behavioral scientists define positive reinforcement (PR+) as “any consequence that causes a behavior to repeat or increase in frequency." Now, I’m not talking about employee of the month ...

The term positive is used to refer to something that is added, and negative is used to refer to something that is removed. Some examples of positive reinforcement may include stickers, toys ...

Reinforcement learning is only one branch of machine learning. It requires extra work for programmers to define clear goals, as well as values for positive and negative outcomes.

Reinforcement learning enables an AI agent to make decisions based on rewards and penalties. A positive outcome of an action is rewarded while a negative outcome is penalized.