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Ellsberg thought experiments and empirical confirmation of Ellsberg preferences pose serious challenges to subjective expected utility theory (SEUT). We have recently elaborated a quantum-theoretic framework for human decisions under uncertainty which satisfactorily copes with the Ellsberg paradox and other puzzles of SEUT. We apply here the quantum-theoretic framework to the Ellsberg two-urn example, showing that the paradox can be explained by assuming a state change of the conceptual entity that is the object of the decision (decision-making, or DM, entity) and representing subjective probabilities by quantum probabilities. We also model the empirical data we collected in a DM test on human participants within the theoretic framework above. The obtained results are relevant, as they provide a line to model real life, e.g., financial and medical, decisions that show the same empirical patterns as the two-urn experiment. [ABSTRACT FROM AUTHOR]

We study a general robust utility maximization problem from terminal wealth and consumption under state constraints. Our framework includes financial models with constrained portfolios, labor income and large investor models. We state the existence and the uniqueness of the consumption–investment strategy by studying the associated quadratic backward stochastic differential equation. We characterize the optimal control by using the duality method and deriving a dynamic maximum principle. [ABSTRACT FROM AUTHOR]

Moral theory has mostly focused on idealized situations in which the morally relevant properties of human actions can be known beforehand. Here, a framework is proposed that is intended to sharpen moral intuitions and improve moral argumentation in problems involving risk and uncertainty. Guidelines are proposed for a systematic search of suitable future viewpoints for hypothetical retrospection. In hypothetical retrospection, a decision is evaluated under the assumption that one of the branches of possible future developments has materialized. This evaluation is based on the deliberator’s present values, and each decision is judged in relation to the information available when it was taken. The basic decision rule is to choose an alternative that comes out as morally acceptable (permissible) from all hypothetical retrospections. [ABSTRACT FROM AUTHOR]

Many quantitative scales are constructed using cutoffs on a continuum with scores assigned to the cutoffs. This paper develops a framework for using or constructing such scales from a decision-making standpoint. It addresses questions such as: How many distinct thresholds or cutoffs on a scale (i.e., what levels of granularity) are useful for a rational agent? Where should these thresholds be placed given a rational agent’s preferences and risk-orientation? Do scale score assignments have any bearing on decision-making and if so, how should scores be assigned? Given two possible states of nature $$\{A, \sim A\}$$ , an ordered collection of alternatives $$\{R_{0}, R_{1},{\ldots}, R_{K}\}$$ from which one is to be selected depending on the probability that A is the case, a simple expected utility condition stipulates when adjacent alternatives are distinguishable and determines the threshold odds separating them. Threshold odds and utilities are mapped onto scale scores via a simple distance model. The placement of the thresholds reflects relative concern over decisional consequences given A versus consequences given ∼ A. Likewise, it is shown that scale scores reflect risk-aversion or risk-seeking not only with respect to A versus ∼ A but also with respect to the rank of the R j . Connections are drawn between this framework and rank-dependent expected utility (RDEU) theory. Implications are adumbrated for both machine and human decision-making. [ABSTRACT FROM AUTHOR]