Optimal Fixed-Budget Best Arm Identification using the Augmented Inverse Probability Estimator in Two-Armed Gaussian Bandits with Unknown Variances. (arXiv:2201.04469v1 [stat.ML])

We consider the fixed-budget best arm identification problem in two-armed
Gaussian bandits with unknown variances. The tightest lower bound on the
complexity and an algorithm whose performance guarantee matches the lower bound
have long been open problems when the variances are unknown and when the
algorithm is agnostic to the optimal proportion of the arm draws. In this
paper, we propose a strategy comprising a sampling rule with randomized
sampling (RS) following the estimated target allocation probabilities of arm
draws …

arm arxiv budget identification ml probability