It is thus also reasonable to ask how we might modify the definition of \(\mathfrak{N}\) so as to obtain a characterization of probabilistic algorithms which we might usefully employ. One answer is embodied in the definition of the class \(\textbf{BPP}\), or bounded-error probabilistic polynomial time.[33] This class can be most readily defined relative to a model of computation known as the probabilistic Turing machine \(\mathfrak{C}\). Such a device \(C\) has access to a random number generator which produces a new bit at each step in its computation but is otherwise like a conventional Turing machine. The action taken by \(C\) at the next step is then determined by the value of this bit, in addition to its internal state and the currently scanned symbol.