On Randomized Dynamic Allocation Indices for the Sequential Design of Experiments
K. D. Glazebrook · Journal of the Royal Statistical Society Series B (Statistical Methodology) · 1980
Summary In response to a suggestion by Bather, Gittins proposed the adoption of rules for sampling one at a time from several Bernoulli populations which were based on randomized versions of his dynamic allocation indices. Such rules, Gittins conjectured, might sometimes be both asymptotically optimal and also (almost) Bayes with respect to the usual discounted reward criterion. This conjecture is investigated and verified.