Reinforcement Learning Part-1 

Re-enforcement learning, which is a machine learning paradigm where an agent learns to make decisions by interacting with an environment. In reinforcement learning (RL), the agent receives feedback in the form of rewards or penalties for actions it takes, and the goal is to learn a policy that maximizes cumulative rewards over time.