"NIPS 2013 Neural Information Processing Systems December 5 - 10, Lake Tahoe, Nevada, USA",,, "Paper ID:","1046" "Title:","Convergence of Monte Carlo Tree Search in Simultaneous Move Games" Reviews First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. This paper studies Monte Carlo tree search in zero-sum extensive form games with perfect information and simultaneous moves. It is proved that the MCTS algorithm converges to an approximate Nash equilibrium under certain conditions. Empirical study confirms the formal result. The detailed comments are as follows. The result is useful and the presentation is clear.

Neural Information Processing Systems http://nips.cc/

Discrete structures play an important role in applications like program language modeling and software engineering.

As mentioned in Section 5.1, our image operation search space for augmentation policies is the following set:

The method needs to search through paths for long-term information, it's like to find conflict facts How to deal with the conflict is not mentioned. In Figure 1, we have "search with only macro stage" ( Random, Reinforce, Bayes) and "with only We will elaborate more on this in Sec. Some recent work on graph alignment were not included in the comparison. The code of VR-GNN [Y e et al. 2019] is not publicly available. The search cost still takes tens of hours.

Neural Information Processing Systems http://nips.cc/

Neural Information Processing Systems http://nips.cc/