Reinforcement Learning vs Supervised Learning

A machine learning approach where an AI agent learns optimal decision-making by taking actions in an environment, receiving rewards or penalties for outcomes, and adjusting behavior to maximize cumulative rewards over time.

A machine learning approach where algorithms learn patterns from labeled training data containing both inputs and correct outputs, enabling prediction of outputs from new unseen inputs after training completes.