The multi-armed bandit (short: bandit) can be seen as a set of real distributions B = \{R_1, \dots ,R_K\}, each distribution being associated with the rewards delivered by one of the K \in \mathbb{N}^+ levers.
A zero-regret strategy is a strategy whose average regret per round \rho / T tends to zero with probability 1 when the number of played rounds tends to infinity [REF].