Thompson Sampling

Thompson Sampling is a heuristic algorithm named after William R. Thompson, designed to address the exploration-exploitation dilemma in the multi-armed bandit problem. This method selects actions that maximize expected rewards by randomly sampling from beliefs, effectively balancing the exploration of unknown environments with the exploitation of known information, making it highly valuable in practical applications.