Review for NeurIPS paper: Online Planning with Lookahead Policies

Additional Feedback: COMMENTS AFTER REBUTTAL Thank you for your response. However, in this paper's case I find that the significance of the paper (i.e., support for your claim that "theoretical results provided in this work are important on their own") is severely lacking without experiments showing a link between this theory and an algorithm's performance in terms of measures like running time, number of 1-step Bellman backups, etc. ***Note: this is not a claim that every theoretical paper needs experiments; it applies only to this specific work, due to the theory issues mentioned in the original review.*** The rebuttal's attempted arguments against providing experiments really miss the mark: -- The rebuttal gives the "Beyond the one step greedy approach in RL" as an example of a paper similar in the degree of its theoretical focus to this submission, but that paper actually has experiments! Light experiments could do the job. That "Beyond the one step greedy approach in RL" paper that you mentioned yourself is a case in point.