As argued in Section 3, it is not only the number of found routes that is important but rather the diversity of routes. To measure this, we find the optimal number of clusters formed by the predicted routes. MCTS seems to fare well in this comparison with a median of 68 for the set-n1 and 77 for the set-n5. Retro* is as successful in finding a diverse set of routes for set-n1, with a median of 68. However, for the set-n2 the diversity is lower with a median number of clusters of 39. Because DFPN gives a low number of routes it is not surprising to see that the median number of clusters is two for both sets of routes. As seen in Figure the distribution of the optimal number of clusters is also skewed. First, there is a sizable portion of the targets for which a relatively small number of clusters (< 10) are found and this is true for all three search methods. Then there is a roughly equal portion of targets for which the number of clusters is more than 10 for MCTS and Retro*. Finally, for Retro* we find a few targets with more than 500 clusters.