Introduction to Multi-Armed Bandit Problems Multi-Armed Bandit (MAB) problems are a class of reinforcement learning problems where an agent has to decide between multiple actions (referred to as “arms”) and receive a reward for their choice. The name “bandit” comes from the analogy of a casino slot machine with multiple Continue Reading