the value of generative adversarial training for model-based reinforcement learning (RL) with offline data, especially

First, we sincerely thank all reviewers for their thoughtful comments and suggestions. We will report the variance and statistical significance of our empirical results in our revision. These shed light on the approach's effectiveness as an online recommender. These two factors help control bias in value estimation for model-based RL. Please refer to Line 9-15 for our responses to possible new empirical evaluations.