In Reinforcement Learning, the performance of learning agents is highly sensitive to choice time discretization. Agents acting at high frequencies have best control opportunities, along with some drawbacks, such as possible inefficient exploration and vanishing action advantages. The repetition actions, i.e., persistence, comes into help, it allows agent visit wider regions state space improve ...