# Recognizing vs Deciding in defining class BPP

In Sipser's text, he writes:

When a probabilistic Turning machine recognizes a language, it must accept all strings in the language and reject all strings not in the language as usual, except that now we allow the machine a small probability of error.

Why is he using "recognizes" instead of "decides"? If the machine rejects all strings that are not in the language, then it always halts, so aren't we restricted to deciders in this case?

The definition goes on:

For $0 < \epsilon < 1/2$ we say that $M$ recognizes language $A$ with error probability $\epsilon$ if

1) $w \in A$ implies $P(M \text{ accepts } w) \ge 1 - \epsilon$, and

2) $w \notin A$ implies $P(M \text{ rejects } w) \ge 1 - \epsilon$.

So it seems like the case of $M$ looping is simply not allowed for probabilistic Turning machines?