Preference Modeling
A method for representing and estimating preferences between possible actions or outcomes to guide an AI system's decision-making.
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Related terms
A learning approach in which an AI system learns from preferences between possible outputs or actions to better align its behavior with desired outcomes.
Utility FunctionA mathematical function that assigns a numerical value to outcomes to represent preferences and guide optimal decision-making.
Reward FunctionA mathematical function that quantifies the feedback or score an agent receives for taking a specific action in a given state.
Decision PolicyA strategy or set of rules that determines how an AI agent selects actions or makes decisions based on goals, inputs, constraints, and current state.
Action SelectionThe process of choosing the most appropriate action from available options based on goals, policies, context, constraints, or expected outcomes.