Reward Function

The process of training a mathematical model to score AI outputs based on human or automated preferences.

A strategy or set of rules that determines how an AI agent selects actions or makes decisions based on goals, inputs, constraints, and current state.

A mathematical function that assigns a numerical value to outcomes to represent preferences and guide optimal decision-making.

The process of choosing the most appropriate action from available options based on goals, policies, context, constraints, or expected outcomes.

A machine learning paradigm where an agent learns to make optimal decisions by taking actions in an environment to maximize cumulative rewards.