I'm studying Reinforcement Learning, and have come across multi-armed bandits.
Why are these called bandits? And why are they armed?
I'm studying Reinforcement Learning, and have come across multi-armed bandits.
Why are these called bandits? And why are they armed?
This is actually explained on the Wikipedia page
This is a classic reinforcement learning problem that exemplifies the exploration–exploitation tradeoff dilemma. The name comes from imagining a gambler at a row of slot machines (sometimes known as "one-armed bandits"), who has to decide which machines to play, how many times to play each machine and in which order to play them, and whether to continue with the current machine or try a different machine.
they even have a picture of few of those:
As noticed by Henry in the comment, there is even more accurate image on Wikipedia to show the etymology:
In section 2.1 of Sutton and Bardo's Reinforcement Learning: An Introduction, they say:
[...] the k-armed bandit problem, so named by analogy to a slot machine, or “one-armed bandit,” except that it has k levers instead of one. Each action selection is like a play of one of the slot machine’s levers, and the rewards are the payout for hitting the jackpot.