 We might add additional structure to the representation: to each probability function, the decision-maker assigns a degree of “reliability”, which tracks how much relevant information the decision-maker has about the states of nature (Good 1952; Gärdenfors &amp; Sahlin 1982). A decision-maker selects a desired threshold level of epistemic reliability. She then considers all probability functions above this threshold, and maximizes the minimum expected utility (Γ-maximin) with respect to these probability functions. (In principle, a different decision rule could be used in this step.) For the decision-maker deciding whether to bet on tennis matches, the above-threshold probability functions for the first match may include only \(p(P1 \text{WINS}) \approx 0.5,\) but for the second and third match may also include \(p(P1 \text{WINS}) \approx 0\); thus betting on P1 in the first match will have a higher value than betting on P1 in the other matches.