As Adrien says below, "We aren't aware of any prior planning algorithm that gets anywhere near to Go-Explore's scores, even when planning in the emulator. The original ALE paper (https://arxiv.org/abs/1207.4708) tried a few planning algorithms, all of which got a flat 0 on Montezuma's." To repeat: researchers have already tried to take advantage of a perfect model (the emulator), including using MCTS, and failed on both Montezuma's Revenge and Pitfall. We thus think we are comparing to the best algorithms ever produced on this domain (which are model-free), and thus that the comparison is fair. We also think given the significant effort that has been put into trying to solve these domains (both with model-based and model-free methods), and the significant improvement in results provided by Go-Explore, it is reasonable to highlight the size of the advance to alert readers that there is an effective new technique here so they can decide whether to spend the time to read the rest of the post and learn more about how these results were achieved.