About this document

Understanding Reinforcement Learning by vedang maheshwari is a document available to read on EtoBox.

Reinforcement learning is a type of machine learning where an agent learns how to achieve a goal by interacting with its environment. The agent performs actions and receives rewards or punishments, allowing it to gradually learn what actions yield the maximum reward. Key aspects of reinforcement learning include the agent, environment, actions, states, rewards, and policies to maximize long-term rewards. Methods like Q-learning use reinforcement learning to find optimal actions by learning action-value func

Author

vedang maheshwari

Language

EN