Reinforcement Learning

Reinforcement Learning (RL) is an area of machine learning where an agent learns to make decisions by interacting with an environment to achieve a specific goal. The agent receives feedback in the form of rewards or penalties based on its actions, which guides it in improving its decision-making over time. The aim is to develop a policy that maximizes the expected cumulative reward, resulting in optimal behavior in various situations.