In the proceedings of the 10th International Conference on Soft Methods in Probability and Statistics (SMPS 2022), pp. 96-–103, Aug. 2022.

Winner of a- doi: 10.1007/978-3-031-15509-3_13
- arXiv: 2204.07428

Given information about which options a decision-maker definitely rejects from given finite sets of options, we study the implications for decision-making with E-admissibility. This means that from any finite set of options, we reject those options that no probability mass function compatible with the given information gives the highest expected utility. We use the mathematical framework of choice functions to specify choices and rejections, and specify the available information in the form of conditions on such functions. We characterise the most conservative extension of the given information to a choice function that makes choices based on E-admissibility, and provide an algorithm that computes this extension by solving linear feasibility problems.