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 ...

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 ...

A/B testing is popular among digital marketers, content strategists and web designers—and for good reason. Apart from increasing a website’s conversion rates, it also improves user engagement, comes ...