Thomson Sampling

Thompson Sampling is a method used in decision-making scenarios where you need to choose among options, like recommending products or testing different website layouts. It works by maintaining a probabilistic belief about how good each option is, based on past results. Then, it randomly selects options according to these probabilities, balancing the need to explore new possibilities and exploit known favorites. This approach helps to efficiently identify the best options over time, improving decisions as more data is gathered, making it widely effective in adaptive learning and optimization tasks.