Abstract
According to the main theorem of the theory of games minimax strategy and risk for the two-armed bandit problem are determined as Bayes ones corresponding to the worst prior distribution. Incomes are assumed to be normally distributed with unit variances and expectations depending on picked alternatives only. In this case asymptotically the worst prior distribution can be chosen a symmetric and asymptotically uniform one. It allows to use numerical optimization. Results can be applied to systems with parallel data processing including distributions different from the normal.
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