Rising Rested MAB with Linear Drift
Abstract
We consider non-stationary multi-arm bandit (MAB) where the expected reward of each action follows a linear function of the number of times we executed the action.
Our main result is a tight regret bound of $\tilde{\Theta}(T^{4/5}K^{3/5})$, by providing both upper and lower bounds.
We extend our results to derive instance dependent regret bounds, which depend on the unknown parametrization of the linear drift of the rewards.
Our main result is a tight regret bound of $\tilde{\Theta}(T^{4/5}K^{3/5})$, by providing both upper and lower bounds.
We extend our results to derive instance dependent regret bounds, which depend on the unknown parametrization of the linear drift of the rewards.
