UCB (C=0) shows trends of the selections in each classification of nodes such as Greedy, but with a less extreme nature due to the use of an average score, thus mitigating the performance degradation. UCB (C=1) follows a trend similar to that of UCB (C=0) but, like Uniform to some extent, initially grows in the fractions of nodes possessing minimum path lengths of 2 and 1 with respect to the number of iteration steps due to a preference for newly found nodes arising from the second exploration term of Eq. 7. Importantly, UCB (C=∞) stands out, with substantially higher fractions of selected nodes possessing minimum path lengths of 2 and 1 compared to those of three baselines, indicating the advantage of the exploration term in selecting nodes near the goal node. This is interpreted as the origin of the best performance of UCB (C=∞) in the goal finding rate among all policies. Among the remaining policies that balance exploration and exploitation, PI and EI show a trend of node selections similar to that of UCB (C=∞), which is purely exploration-based, whereas TS deviates from UCB (C=∞) to some extent, implying a more exploitation-influenced. Thus, by characterizing the node selection fractions, we gained a more detailed understanding of the differences and similarities between the performances of the node selection policies. and Random has the worst performance (c.f., Greedy in the Passerini reaction in Figure ).