Concepts for decision making under severe uncertainty with partial ordinal and partial cardinal preferences
The authors introduce three different approaches for decision making under uncertainty if (i) there is only partial (both cardinally and ordinally scaled) information on an agent's preferences and (ii) the uncertainty about the states of nature is described by a credal set (or some other imprecise probabilistic model). They: (1) Rely on decision criteria constructing complete rankings of the available acts that are based on generalized expectation intervals; (2) Introduce different concepts of global admissibility that construct partial orders between the available acts by comparing them all simultaneously; (3) Define criteria induced by suitable binary relations on the set of acts and, therefore, can be understood as concepts of local admissibility; (4) Provide linear programming based algorithms for checking optimality/admissibility of acts; (5) Include a discussion of a prototypical situation by means of a toy example.
scientific article; zbMATH DE number 6893199
scientific article