From Ambiguity Aversion to a Generalized Expected Utility. Modeling Preferences in a Quantum Probabilistic Framework
Diederik Aerts, Sandro Sozzo

TL;DR
This paper introduces a quantum probabilistic framework for modeling human decision-making under ambiguity, successfully representing data from Ellsberg and Machina paradoxes and enabling a generalized expected utility theory.
Contribution
It develops a quantum-based model that captures ambiguity preferences and addresses limitations of classical theories, offering a flexible approach to decision under uncertainty.
Findings
Quantum model accurately fits data from Ellsberg and Machina experiments.
The framework describes subjective attitudes towards ambiguity.
It enables a state-dependent expected utility formulation.
Abstract
Ambiguity and ambiguity aversion have been widely studied in decision theory and economics both at a theoretical and an experimental level. After Ellsberg's seminal studies challenging subjective expected utility theory (SEUT), several (mainly normative) approaches have been put forward to reproduce ambiguity aversion and Ellsberg-type preferences. However, Machina and other authors have pointed out some fundamental difficulties of these generalizations of SEUT to cope with some variants of Ellsberg's thought experiments, which has recently been experimentally confirmed. Starting from our quantum modeling approach to human cognition, we develop here a general probabilistic framework to model human decisions under uncertainty. We show that our quantum theoretical model faithfully represents different sets of data collected on both the Ellsberg and the Machina paradox situations, and is…
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