 Infinite precision cannot be required: rather, in any given context, there must be some finite tolerance—some positive threshold such that ignoring all outcomes whose probabilities lie below this threshold counts as satisfying the norm…. There is a norm of decision theory which says to ignore outcomes whose probability is zero. Because this norm mentions a specific probability value (zero), it is the kind of norm where it makes sense to impose a tolerance: zero plus or minus \(\epsilon\) (which becomes zero plus \(\epsilon,\) given that probabilities are all between 0 and 1)… the idea behind (RNP) is that in any actual context in which a decision is to be made, one never needs to be infinitely precise in this way—that it never matters. There is (for each decision problem, each lottery therein, and each agent) some threshold such that the agent would not be irrational if she simply ignored outcomes whose probabilities lie below that threshold. (Smith 2014: 472–474)