Before revision:  In this work , we propose a REPresentation-And-INstance Transfer algorithm (REPAINT) for deep actor-critic reinforcement learningparadigm. In representation transfer, we adopt a kickstarted training method using a pre-trained teacher policy by introducing an auxiliary cross-entropy loss.
After revision:  In this work , we propose a REPresentation-And-INstance Transfer algorithm (REPAINT) algorithm for knowledge transfer in deep reinforcement learning. REPAINT not only transfers the representation of a pre-trained teacher policy by introducing an auxiliary cross-entropy loss.