About this document

Understanding Reinforcement Learning Concepts by Kelechi is a document available to read on EtoBox.

Reinforcement learning is a machine learning technique where an agent learns to achieve goals in complex environments through trial-and-error using rewards. The agent learns to make sequences of decisions to maximize rewards. Key concepts include states, actions, environments, and rewards. Traditional machine learning requires labeled data while reinforcement learning uses rewards to guide learning without explicit instructions on how to achieve goals.

Author

Kelechi

Language

EN