The evaluation value for the molecules of the newly added child node is used as the reward. The reason for this is that unlike board games where the terminal state can be easily determined, it is difficult to perform a rollout in molecular generation due to the ambiguity of the terminal state. For example, the benzene ring is non-terminal when naphthalene is generated, but it is terminal when benzene ring is generated. Existing methods use machine learning models to determine if the state is terminal, or to fix the number of steps. However, when the search starts from an arbitrary molecule and proceeds in the direction of increasing and decreasing atoms, as in this method, determining whether the search is terminated is difficult, because the initial molecule is already completed. Another reason is that deep nodes are likely to deviate significantly from the initial molecule, which is not in accordance with the purpose of the study.