public class UCBPoolBasedActiveDyadRanker
extends ARandomlyInitializingDyadRanker
A prototypical active dyad ranker based on the UCB decision rule. During the
learning procedure, it keeps track over the standard deviation of the skill
values predicted for a dyad. First a constant number of random queries is
sampled at the beginning. Then the sampling strategy randomly selects problem
instances and picks the two dyads with largest skill + standard deviation for
pairwise comparison. On each query step, this is repeated a constant number
of times to create a minibatch.