Before revision:  In representation transfer, we adopt a kickstarted training method using a pre-trained teacher policy by introducing an auxiliary cross-entropy loss. In instance transfer, we develop a sampling approach, i.e., advantage-based experience replay, on transitions collected following the teacher policy , where only the samples with high advantage estimates are retained for policy update.
After revision:  In representation transfer, we adopt a kickstarted training method using a pre-trained teacher policy in the on-policy learning, but also uses an advantage-based experience replay, on transitions collected following the teacher policy , where only the samples with high advantage estimates are retained for policy update.