Currently, I am reading into the Multi-Armed-Bandit problem and found the special case of non-stationary (environment and its attributes, like the reward distribution, change over time) stochastic environments. Since this is an adversarial MAB problem, no context is available at the moment. I've read that $\epsilon$-greedy, Exp3 and the FPL algorithm work. But some tutorials like TensorFlow ones use LinUCB and other algorithms, which are never mentioned in any papers.
So, my question is, basically: which algorithms work on the non-stationary stochastic environments?