Universal Best Arm Identification.

In this paper, we study the problem of universal best arm identification in multi-armed bandits, where the underlying setting can be either stochastic or adversarial and is not revealed to the forecaster a priori. We propose an algorithm, called S3-BA, that identifies the best arm without prior knowledge of the underlying setting. The key idea is to simultaneously explore the arms and learn the pr...