The accuracies for the predictions on the set-n5 routes are significantly lower, with the best-observed top-1 around 0.10 and the best top-10 around 0.42 (see Table ). This shows more than the fraction of solved routes that set-n5 is a challenging set for any route prediction method. MCTS slightly outperforms Retro*, but it is unclear if the differences are practically relevant. There is a trend that the fraction of targets for which a shorter route than the reference route was found in top-1 is greater than for the set-n1 routes. And it is also clear that the leaves overlap in top-1 is decreased compared to the set-n1 routes. What this analysis show is that all of the methods are in need of improvements when it comes to finding long and convergent routes. All of the three search methods can predict shorter routes, which in Table is shown as a high fraction of solved targets, but they struggle to recover the humanlike reference routes.