The Upper Confidence Bound (UCB) algorithm is a prominent method in the realm of reinforcement learning that effectively addresses the exploration-exploitation tradeoff, a fundamental challenge in decision-making processes. This tradeoff involves balancing the need to explore new actions to discover their potential rewards (exploration) with the need to exploit known actions that yield high rewards