Humans count to indefinitely large numbers by recycling words from a finite list, and combining them using rules--for example, combining sixty with unit labels to generate sixty-one, sixty-two, and so on. Past experimental research has focused on children learning base-10 systems, and has reported that this rule learning process is highly protracted. This raises the possibility that rules are slow to emerge because they are not needed in order to represent smaller numbers (e.g., up to 20). Here, we investigated this possibility in adult learners by training them on a series of artificial number "languages" that manipulated the availability of rules, by varying the numerical base in each language. We found (1) that the size of a base--for example, base-2 versus base-5--had little effect on learning, (2) that learners struggled to acquire multiplicative rules while they learned additive rules more easily, (3) that memory for number words was greater when they were taught as part of a sequential count list, but (4) that learning numbers as part of a rote list may impair the ability to map them to magnitudes.