e6d8545daa42d5ced125a4bf747b3688-AuthorFeedback.pdf

The common specifications in Appendix D are just detailed descriptions of each hyperparameter used in Nature7 DQN paper that we applied to all the baselines and our method for the experiment. Many of the recent reinforcement learning methods require changes in the network structures or require additional20 memory structures (Ephemeral Value Adjustments, RUDDER). The idea of the backward update is not novel and we have stated in section 3.1 that the tabular backward update26 (Algorithm 1) is a special case of Lin's method (1992). The training process of the adaptivescheme is described in Appendix34 A.AlltheKnetworksaretrained using thesame sample episode atthesame time.