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Abstract: We integrate the necessary components and demonstrate a proof-of-concept for a "robot physicist" that is able to plan the next experiment needed to most efficiently measure a fundamental constant of nature. First we apply the algorithm to toy data generated from a Gaussian distribution, then we apply the algorithm to data obtained from a simulated physics experiment.