Pedro Braga

Prioritizing Samples in Reinforcement Learning with Reducible Loss

Most reinforcement learning algorithms take advantage of an experience replay buffer to repeatedly train on samples the agent has observed in the past. Not all samples carry the same amount of significance and simply assigning equal importance to each of the samples is a naïve strategy. In this pape…