Interactive reinforcement learning has allowed speeding up the process in autonomous agents by including a human trainer providing extra information to agent real-time. Current interactive research been limited real-time interactions that offer relevant user advice current state only. Additionally, provided each interaction is not retained and instead discarded after single-use. In this work, w...