Bandits algorithms

Bandit algorithms are decision-making tools that help balance exploring new options and exploiting known successful ones. Imagine facing multiple slot machines (bandits), each with different payout chances. The goal is to maximize winnings by choosing which machines to play, learning from each outcome. These algorithms intelligently decide when to try unfamiliar options (exploration) and when to stick with known winners (exploitation). They are used in various fields like online advertising, recommendation systems, and clinical trials, optimizing choices over time to achieve the best possible results with limited information.