Multi-Armed Bandit Problem

The Multi-Armed Bandit problem involves choosing among multiple options (or "arms") to maximize rewards over time. Imagine a row of slot machines, each with different odds of payout. You want to figure out which machine is best, but initially, you have limited information. As you try each machine, you learn about their payouts and adjust your choices accordingly. The challenge is balancing exploration (trying different machines to gather information) with exploitation (favoring the machine that has paid out the most so far). The goal is to develop a strategy that maximizes your total reward through efficient decision-making.