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 ...

The multi-armed bandit (MAB) metaphor encapsulates the challenge of sequential decision-making under uncertainty, where a decision-maker repeatedly chooses among competing options (or “arms”) and ...

You know that computers can beat humans at lots of games. But so far, humans are still better than the most powerful systems when playing at Chinese strategy game Go. The reason is simple: computer ...