Decision Theory

A Markov Decision Process is a mathematical framework for modeling decision-making in situations where outcomes are partly random and partly under the control of a decision maker.

A Multi-Armed Bandit is a problem in decision-making where a player must choose between multiple options with uncertain rewards.

Regret Minimization is a decision-making strategy aimed at reducing potential regrets over choices made.

Thompson Sampling is a method for making decisions in uncertain situations, balancing exploration and exploitation.

The Upper Confidence Bound is a statistical method used in decision-making to estimate the upper limit of a parameter's value.

A utility function quantifies preferences over a set of choices, helping to model decision-making in economics and AI.