3 Lam, S.K. Pennock, D.M. Cosley, D. Lawrence, S 2003 Uncertainty in Artificial Intelligence (UAI2003) Acapulco, Mexico 337-345 We exploit the redundancy and volume of information on the web to build a computerized player for the ABC TV game show “Who Wants To Be A Millionaire?”. The player consists of a questionanswering module and a decision-making module. The question-answering module utilizes question transformation techniques, natural language parsing, multiple information retrieval algorithms, and multiple search engines; results are combined in the spirit of ensemble learning using an adaptive weighting scheme. Empirically, the system correctly answers about 75% of questions from the Millionaire CD-ROM, 3rd edition—general-interest trivia questions often about popular culture and common knowledge. The decision-making module chooses from allowable actions in the game in order to maximize expected risk-adjusted winnings, where the estimated probability of answering correctly is a function of past performance and confidence in correctly answering the current question. When given a six question head start (i.e., when starting from the $2,000 level), we find that the system performs about as well on average as humans starting at the beginning. Our system demonstrates the potential of simple but well-chosen techniques for mining answers from unstructured information such as the web. http://www.grouplens.org/papers/pdf/1m-uai2003.pdf