Multi-armed bandits (MAB) is a peculiar Reinforcement Learning (RL) problem that has wide applications and is gaining popularity. Multi-armed bandits extend RL by ignoring the state and try to balance ...

How does a gambler maximize winnings from a row of slot machines? This is the inspiration for the "multi-armed bandit problem," a common task in reinforcement learning in which "agents" make choices ...