# Do xgboost and random forests in general handle multiple splits of the same numeric feature in a single branch?

For example, let's say that the age (say $x$) of a person for $12< x< 25$ can be used to predict computer usage to a high degree of certainty. In a decision tree, this could be represented by a split of $x<25$ followed by a split of $x>12$.

Does xgboost, or other decision tree learning algorithms in general, handle multiple splits within the same branch?