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A Waldian may then have preferences over acts that are not in agreement with subjective expected utility but always chooses as if she was a subjective expected utility maximizer.
On the other hand, there is no way of extended the self-torturer's preferences so that he can be represented as an expected utility maximizer.
The perfectly rational expected utility maximizer as depicted in Figure 1a is then obtained from Equation (18) by taking the limit α→∞.
This is so because such a convention couldn't get established (or couldn't be sustained) if people were aware that everyone was a consistent utility maximizer of the act utilitarian sort.
Jane's preferences can be extended, by adding new preferences without removing any of the ones she has, in a way that lets us represent her as an expected utility maximizer.
Although Seidenfeld, Kadane, and Schervish have shown that there is generally no way to define an aggregate Bayesian expected utility maximizer to represent the Pareto preferences of a group of two or more individual Bayesian expected utility maximizers, there is no impossibility result precluding the aggregation of individual probabililty assignments into a group probability assignment.
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Specifically, we adopted a choice model derived in a random utility maximization model (RUM) framework, in which decision makers are assumed to be utility maximizers.
This conflict has generated a huge literature, which almost always assumes that individuals are expected utility maximizers.
This evidence demonstrates that human behavior deviates in systematic ways from the idealized behavior attributed to expected utility maximizers in particular, and to "rational economic man" in general.
Schwartz makes his case mostly through research in psychology and behavioral economics — research that shows how far real people are from the perfectly rational "utility maximizers" posited by classical economists.
We argue that the patterns in the data are consistent with a model in which police officers are utility maximizers, a fraction of which have a preference for discrimination, who incur relatively high expected costs of officer-involved shootings.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com