Venue: ICLR 2020 Conference

Reviews:

final_score: rating: 1: Reject
review_content: This paper tries to improve exploration performed by alphazero in a game of tic-tac-toe using MCTS. The paper proposes to use master game tree (which is MCTS as well) to control the generation of episodes when solving a game using MCTS.
This is a clear case of less than half-baked paper. The paper does not cite any previous research (no references) and is poorly written. I believe this is sufficient ground for not recommending accept. I would suggest the authors to re-submit when the paper is complete, maybe, start with related work and references.
review_title: Official Blind Review #1

final_score: rating: 1: Reject
review_content: Badly and unprofessionally written

I had and still have a hard time to report what this paper is about. Generally, I can tell probably this paper study the Monte Carlo Tree Search-based methods in the field of Reinforcement Learning. 

The paper is badly written with grammatical issues almost in all the sentences. I definitely urge the author(s) to take the writing significantly more seriously. I almost all the time do not end up rejecting a paper due to the lack of clear writing, but for this paper, unfortunately, despite spending time, I could not understand the paper.


Comments beside the grammatical issues:
I am sorry but I could not understand the abstract.
What does the author(s) mean by "In this research, the
coordination of episode generation was focused on." Same issue with almost all the sentences in the abstract. Unfortunately, I could not follow any of them. Moreover, this paper is full of inaccurate and unjustified statements. Furthermore, again, unfortunately, this paper does not represent even the preliminary elements of scientific writing.


I decided to provide further comments, but sadly I had to change my mind because otherwise, I had to write at least one paragraph of explanation for each paragraph of this paper. With that regard, I do not think it is an appropriate way to utilize the review process. But I would be happy to provide more abstract comments upon request. 
review_title: Official Blind Review #2

final_score: rating: 1: Reject
review_content: This paper appears to be attempting to improve Monte Carlo tree search, though it's not clear how. The paper is very poorly written, with many incomprehensible passages. Moreover there are no references at all. It does not appear to be a serious academic endeavor, merely a set of notes. There are many mathematical symbols not defined, much of the paper consists of blank space yet it goes up to 10 pages, the algorithm boxes are very difficult to follow, the writing is so poor that I cannot decipher what the intent even was. A significant amount of work would be required to make this acceptable for publication in any venue.
review_title: Official Blind Review #3

Meta-review: This paper is a clear reject. The paper is very poorly written and contains zero citations. Also, the reviewers have a hard time understanding what the paper is about.
Decision: Reject