Many decisions are required to be made under uncertainty. The classical approach is to model uncertainty using a belief model based on Zadeh’s fuzzy sets of priors with a utility index reflecting possible consequences, such as a maxmin expected utility (MEU) or Choquet expected utility (CEU). The authors of this work have studied MEU and CEU in the context of Chateauneuf and Faro’s confidence function.

The authors assert that a function based on a probability measure of a likely consequence (probability function) could be used as a confidence measure in the sense of Zadeh’s theory. They assert that an integral function of the probability function(s) could be used to model uncertainty. Through a mathematical analysis based on a set of assumptions on the probability function(s), the authors attempt to establish that MEU and CEU are cases of their approach.

I do not see the benefits of the approach, as the probability functions are deemed to be subjective and are assigned by the decision maker. If some case studies were given, that might provide some evidence of the approach’s benefits.

The paper is quite heavy on mathematical analysis and is vague in parts. At times, this makes it difficult to decipher what is being asserted.