Sample Complexity of an Adversarial Attack on UCB-based Best-arm Identification Policy. (arXiv:2209.05692v1 [cs.LG])

In this work I study the problem of adversarial perturbations to rewards, in
a Multi-armed bandit (MAB) setting. Specifically, I focus on an adversarial
attack to a UCB type best-arm identification policy applied to a stochastic
MAB. The UCB attack presented in [1] results in pulling a target arm K very
often. I used the attack model of [1] to derive the sample complexity required
for selecting target arm K as the best arm. I have proved that the stopping …

arm arxiv complexity identification policy