Off-policy vs On-Policy vs Offline Reinforcement Learning Demystified!

In this article, we will try to understand where On-Policy learning, Off-policy learning and offline learning algorithms fundamentally differ. Though there is a fair amount of intimidating jargon in reinforcement learning theory, these are just based on simple ideas. Reinforcement Learning is a subfield of machine learning that teaches an agent how to choose an action from its action space. It interacts with an environment, in order to maximize rewards over time. Complex enough? let's break this definition for better understanding.